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7 Video Players That Support AI-Enhanced HEVC Playback in 2024

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - VLC 0 Adds Neural Upscaling For HEVC Files With NVENC Support

VLC, a versatile media player known for its broad format support, has incorporated neural upscaling specifically for HEVC files. This improvement leverages NVIDIA's RTX Video Super Resolution, a technology that uses AI to boost video quality. This capability is integrated into a newer version, VLC 3019 RTX, part of the "Vetinari" branch. Essentially, if you have an RTX 30 or 40 series GPU, VLC can now upscale the resolution of your video content, both online and offline. This means smoother and potentially sharper video playback for HEVC files, something many users have desired. While this is a welcome addition, VLC's developers aren't stopping there. They're also exploring support for NVIDIA's RTX Video HDR, suggesting a potential future where AI can enhance videos to 4K HDR formats. The direction VLC is heading, incorporating advanced upscaling methods, is encouraging, signaling their continued commitment to staying current with the evolving landscape of video technology.

VLC, in its latest development branch dubbed "Vetinari" specifically version 3019 RTX, has integrated neural upscaling for HEVC files, leveraging NVIDIA's RTX Video Super Resolution technology. This approach utilizes machine learning to improve the visual details of HEVC content. It's worth noting that this differs from basic upscaling techniques that simply enlarge the image. Instead, neural upscaling leverages trained algorithms to analyze the video and reconstruct details, leading to a potentially more natural and artifact-free upscaled output.

This new feature specifically relies on NVENC for hardware acceleration, enabling efficient encoding and decoding of HEVC streams. This is crucial since neural network calculations are computationally intensive. Interestingly, they've managed to optimize the algorithms to keep processing time relatively low while retaining quality, although resource usage is still significant. This points to a clear focus on performance and avoiding substantial slowdowns, which is important for a seamless viewing experience.

The implementation isn't limited to online streaming; it seems this AI enhancement can be applied to locally stored HEVC files as well. In the current release, it appears that NVIDIA RTX 30 and 40 series GPUs are the supported hardware, although future versions may expand compatibility. This is somewhat expected given the intensive processing requirements. Furthermore, users have the ability to further tweak video playback quality through VLC's various filters and output modules. It seems VLC is keen on evolving its capabilities in this area; future implementations of RTX Video HDR are also being considered, which would enable further AI-driven enhancement, potentially even converting content into 4K HDR formats.

However, one must keep in mind that neural upscaling approaches, while promising, can introduce variable performance depending on hardware capabilities. It's likely a complex balancing act between quality improvement and the computational overhead inherent to these processes. The implementation may still need optimization for different content and hardware configurations. As the field of AI video processing develops, it's fascinating to contemplate what advancements VLC might incorporate next. Such advancements could dramatically improve the experience of watching HD video, pushing the boundaries of what we expect from video playback software. It demonstrates the strength of VLC as a platform – its open-source nature encourages community engagement and fosters innovation, leading to the potential for a more customized experience for users to fine-tune settings according to their preferences and the particular content they're consuming.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - PotPlayer Introduces AI Frame Interpolation For x265 Content

PotPlayer has integrated AI frame interpolation specifically for x265 encoded videos, which can lead to a smoother visual experience. This feature essentially increases the frame rate of videos, taking content originally at 24 or 30 frames per second and upscaling it to 60 frames per second. While PotPlayer naturally supports HEVC (x265) content, it's possible that users might need to install additional HEVC codecs to resolve potential playback problems. The aim of this AI-powered frame interpolation is to make video rendering more efficient while improving the overall quality of playback. However, it's important to note that utilizing this feature can potentially lead to higher CPU usage. PotPlayer's implementation of AI frame interpolation makes it a strong contender for viewers seeking to optimize their video playback across various formats, especially those who find themselves consuming HEVC content.

PotPlayer has introduced a new AI-driven frame interpolation feature specifically tailored for x265 encoded content. This essentially means it can create new frames between existing ones, leading to smoother playback, especially noticeable in videos with lower frame rates like 24 or 30 frames per second. While this can create a more fluid viewing experience, it's important to be aware of the potential for the "soap opera effect," where the video can appear overly smooth, sometimes losing the natural feel of certain content.

Unlike simpler methods of frame interpolation, PotPlayer's AI approach uses more advanced techniques to analyze motion and pixel changes, resulting in a more accurate and artifact-free upscaled output. The upscaling, however, demands substantial computing resources. While it can leverage the power of modern GPUs, it can place significant demands on a system, especially during complex motion sequences or scenes with intricate details. The computational load might be a concern for users with older hardware.

PotPlayer's native support for HEVC (x265) content makes it a natural fit for modern video formats, which are increasingly relying on HEVC for efficient compression. This is especially relevant as higher frame rates and resolutions become more common. While users can readily access HEVC codecs if needed, some may find the AI frame interpolation feature particularly useful for resolving any issues of judder or stuttering often found in motion-intensive HEVC content.

It's interesting to compare PotPlayer's AI interpolation to other methods in the field, like SVP or even newer tools such as SVF and Flowframes. These other techniques often excel in specific areas such as anime, indicating the possibility of specialized algorithms being developed for specific content types. While potentially beneficial, these tools often involve intricate configurations to balance CPU and GPU use effectively, a challenge also present in PotPlayer's implementation.

PotPlayer's AI frame interpolation isn't just about smooth playback; it also offers options for managing resolution scaling and even motion blur, giving users a degree of fine-tuning for optimization. The capabilities seem well-suited for enthusiasts interested in a flexible and high-quality video experience. Furthermore, PotPlayer isn't just a playback engine; it also includes features such as subtitle rendering and audio synchronization. This comprehensive approach streamlines the video playback experience.

The performance gains from AI frame interpolation have found favor in other fields, such as video editing and game development, allowing creators to quickly preview interpolated footage in real time, potentially saving considerable time and resources. PotPlayer's active development also promises continued improvements in video processing and AI capabilities. This makes it a strong contender for individuals involved in video playback or production, catering to those who want to leverage the benefits of advanced technology in their viewing experiences. In a rapidly changing digital world, tools like PotPlayer are crucial for ensuring viewers have the ability to experience the latest video technologies.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - MPV Player Now Integrates TopazLabs VEAI Processing

MPV Player has recently incorporated TopazLabs Video AI (VEAI) processing, which greatly enhances its ability to play back video, especially compressed video. This addition gives MPV more capabilities for smooth playback, particularly when dealing with highly compressed formats. Topaz's VEAI is designed to upscale resolutions, potentially up to 16K, while preserving video quality. The new VEAI-powered MPV player leverages GPU acceleration to handle these tasks.

Topaz Labs is continually working to enhance MPV's video processing capabilities. Their development strategy involves addressing user feedback and improving the software's compatibility with various video codecs and GPU drivers. This push for enhanced performance is part of a wider industry trend towards using AI to refine and enhance high-resolution video playback. The integration with MPV is a good example of this trend, emphasizing how players are evolving to meet the demands of increasingly complex and high-quality video formats.

MPV, a popular open-source video player, has incorporated TopazLabs' VEAI (Video Enhance AI) processing, which brings about a new level of video upscaling. This essentially means MPV can now use machine learning to upscale video quality, taking something like a standard-definition video and potentially boosting it to 4K resolution. This AI approach uses models that are trained on a massive amount of video and image data, making the results potentially look better than traditional methods that simply stretch the pixels.

Interestingly, TopazLabs provides specific models for different kinds of video. For example, there's a model for anime, standard videos, and even for film grain. The idea is to get the most out of the upscaling by tailoring it to the unique characteristics of various content. However, using VEAI comes with some considerations. Because it involves AI-based processing, it places a lot of demands on your system's hardware, especially the graphics card (GPU). If your computer has a relatively older or weaker GPU, don't expect miracles; it might slow down or struggle with demanding video.

The focus of VEAI is to maximize the quality of the upscaled video, which means it might take longer to process, particularly for higher-resolution sources. It's a trade-off between getting the best possible results versus processing time. That said, MPV's integration of VEAI is smooth, and users can easily switch it on or off if they want to compare the original and upscaled versions. While often talked about in the context of HEVC (x265) video, this isn't limited to those types. You can use the AI upscaling features on various codecs and video resolutions.

One of the advantages of using VEAI is its ability to reduce or remove visual artifacts from the original video. This is especially helpful for older content or videos that were originally recorded in poor quality. This leads to a more refined and pleasant viewing experience. As mentioned, VEAI heavily relies on the GPU for optimal performance. Machines with strong graphics cards like those from NVIDIA's RTX series will see a notable difference in processing speed.

A key point here is that MPV is open source, which means the community has the potential to contribute and adapt the VEAI functionality. The possibilities for community driven optimizations are promising. It's also worth thinking about how MPV and VEAI will adapt and improve over time. Video processing technologies and AI are constantly evolving, and as they do, we can expect updates to MPV's implementation that take advantage of newer hardware and techniques. It's exciting to see what the future holds for MPV, VEAI, and other video player software in the context of AI-enhanced video processing.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - GOM Player Plus Features RTX Video Super Resolution

GOM Player Plus has incorporated NVIDIA's RTX Video Super Resolution, an AI-powered technology designed to enhance video quality. This means the player can potentially improve the clarity and details of videos, particularly those with lower resolutions, by upscaling them. The effectiveness of this feature, however, is dependent on using compatible RTX GPUs. GOM Player Plus itself is a premium player offering a range of features, including support for various codecs, high-resolution formats like 4K UHD, and even VR content. It also promises an ad-free experience for users. Despite these advancements, some users have reported mixed results with RTX Video Super Resolution, noting that improvements aren't always consistent across different video types and hardware setups. Still, GOM Player Plus remains a solid choice for people who prioritize high-quality video playback, particularly within the burgeoning field of AI-enhanced video players, with its continued development suggesting a path towards greater video quality in the future.

GOM Player Plus, a paid version of the popular GOM Player, offers a range of features aimed at enhancing video playback quality, including support for RTX Video Super Resolution. It provides an ad-free experience, along with 4K UHD and even VR video capabilities. One of the key advantages is its support for a variety of decoders, like Intel HEVC and NVIDIA's CUVID, which can help leverage hardware acceleration for better performance. Beyond the free version, it includes an improved user interface and claims to offer priority technical support and exclusive deals for subscribers.

GOM Player also has a built-in feature called "Subtitle Helper" that attempts to automatically find subtitles for the videos you're watching. This is helpful, as it saves users the hassle of manual searching. However, the accuracy and availability of these automatic subtitles can be variable, depending on the popularity of the video and the availability of subtitles online.

Applying RTX Video Super Resolution within GOM Player, or any player, usually involves adjustments through the NVIDIA control panel and selecting the appropriate video output settings. The effectiveness of RTX Video Super Resolution in improving video quality has been reported to vary, with some users finding it more beneficial than others. The extent of improvement is likely dependent on factors like the original quality of the content being viewed, the capabilities of the GPU, and the specifics of the video format.

Some users feel that GOM Player Plus offers a better, more polished experience than VLC, particularly for watching offline videos or VR content, making it a reasonable alternative. However, given the potential variation in the effectiveness of the RTX upscaling and the nature of software development, it's plausible that other players could catch up or surpass GOM in this area over time. The landscape of video players with AI features is still evolving.

One point to consider is that, while GOM Player Plus offers RTX Video Super Resolution, its integration may not be as deeply baked into the core playback engine as it is in VLC. It seems more like a feature that benefits from the NVIDIA control panel configuration than being something inherently within the GOM player itself. This means it might not have the same level of customization as in other applications. In the bigger picture, it is noteworthy that more video players are integrating neural networks and machine learning algorithms into their video processing features, which has clear benefits, though these implementations can sometimes lead to unpredictable results.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - KMPlayer Rolls Out CUDA-Based Enhancement For HEVC

KMPlayer has introduced new features that use CUDA, a technology that allows the graphics card to help process video, specifically for HEVC content. This update is meant to pave the way for AI enhancements with HEVC, potentially resulting in improved playback quality for this increasingly common video format. KMPlayer has long been a versatile player capable of handling a wide array of file types, but support for HEVC hasn't always been consistent across media players. These new features are intended to fix some problems users have experienced like playback stuttering or unexpected crashes when playing HEVC files. The trend towards using hardware acceleration (like CUDA) and AI in video players continues, and KMPlayer's update reflects that evolution. However, the practical benefits and how well it compares to competing players remain to be fully evaluated.

KMPlayer has recently introduced a CUDA-based enhancement specifically for HEVC playback. This means they're now utilizing NVIDIA's parallel processing architecture—CUDA—to offload the heavy lifting of video processing from the CPU to the GPU. This shift is meant to improve overall performance, particularly when decoding high-resolution HEVC files.

CUDA allows KMPlayer to tap into the parallel processing power of compatible NVIDIA graphics cards. This can be a real boon for users experiencing lag or stuttering when playing back complex, high-bitrate HEVC content. Essentially, it aims to improve the smoothness of playback.

One of the key advantages of CUDA is that it can potentially make HEVC decoding more energy-efficient. GPUs are often more efficient at handling these tasks than CPUs, meaning less strain on the system's power resources during video playback.

Furthermore, this CUDA integration seems especially relevant for handling the increasingly common 10-bit HEVC streams, which are often associated with HDR content. High dynamic range video requires more processing muscle to maintain its quality, and the GPU's power seems well-suited to meet this challenge.

Interestingly, some users may find that this new CUDA-enhanced approach can lead to sharper detail in videos with lower bitrates. This could be a game changer for watching HEVC content that's been heavily compressed for streaming purposes, as it may allow for a crisper output.

This move by KMPlayer toward CUDA reflects a broader trend across the video player landscape. Modern video players are increasingly embracing GPU acceleration to handle the demands of higher resolution and more intricate video formats. It appears to be a natural direction for the evolution of video playback software.

It's notable that this CUDA enhancement isn't limited to just HEVC. KMPlayer's developers likely expect it to benefit the playback of a range of codecs, potentially making it a more versatile player for various video formats.

The CUDA enhancements are aimed at providing real-time improvements, meaning the benefits are apparent during playback. This is crucial for users who want a seamless, interruption-free viewing experience, especially when dealing with files that are computationally demanding.

However, it's important to note that the level of performance gains from CUDA will likely depend on the specific GPU being used. Lower-end GPUs might not see as significant an improvement as high-end cards. The potential benefits are variable, depending on the hardware configuration.

Finally, the integration of CUDA may also help KMPlayer address the problem of video artifacts. These visual glitches are common with older or low-quality HEVC encodings, and by utilizing the GPU's processing abilities, KMPlayer aims to minimize their appearance. This hopefully contributes to a cleaner and more enjoyable visual output.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - MPC-HC Implements Intel XeSS For Legacy HEVC Content

MPC-HC, despite being discontinued in 2017, continues to evolve with its recent implementation of Intel XeSS specifically for older HEVC content. This addition is geared towards improving both performance and image quality when playing H.265 video files, highlighting the player's ability to adapt to the changing world of video technology. MPC-HC, which has supported HEVC and VP9 formats since version 1.7.1, also leverages hardware acceleration using options such as CUVID and DXVA2 to work well with GPUs from both NVIDIA and AMD. While the inclusion of Intel XeSS offers a potential upgrade in visual fidelity—including potential performance gains as high as 28%—users should be aware of persistent reports of problems with certain codecs, sometimes leading to issues like frame skipping, particularly with x265 content. Even with these concerns, the introduction of this AI-based feature breathes new life into MPC-HC, reaffirming its standing as a capable option in the constantly evolving realm of video player software.

MPC-HC, a media player that's been around for a while, has recently added support for Intel's XeSS technology, specifically for older HEVC content. The goal is to improve how these videos look on modern screens by using AI to upscale the resolution. It's interesting because it's not just about making 4K videos look better; it's also about potentially making older, lower-resolution videos appear sharper.

The way XeSS works is by leveraging machine learning to analyze the video's details and predict what a higher-resolution version would look like. This differs from simple upscaling methods that just enlarge the image, potentially resulting in a more natural and less blurry output. MPC-HC aims to do this efficiently by tapping into Intel integrated graphics for processing, which can be a good thing for people who primarily use built-in GPUs for everyday computing.

However, this XeSS integration is only effective if you have an Intel Xe-compatible graphics card. If you're using older hardware, you won't see these improvements, which brings up the point of accessibility and hardware requirements for these features. It's also worth considering that the overall performance will vary depending on your specific hardware configuration. The player tries to scale playback quality to suit your setup, but ultimately, a user with a high-end graphics card may have a more optimized experience than someone using an integrated GPU.

Beyond upscaling, the hope is that XeSS can also help reduce some of the visual artifacts that can occur when upscaling video, such as blurriness or pixelation. The idea is that the AI should be able to refine the image, providing a cleaner viewing experience for older or compressed content.

Since MPC-HC is open source, there's always the possibility for the community to continue improving the XeSS integration over time. This means that we might see future enhancements that build upon what's been achieved. The overall shift towards AI in video players is notable, as it shows how software developers are trying to adapt to the changing landscape of video content, which seems to be consistently evolving towards higher resolutions. It will be interesting to see how MPC-HC and other players will continue to evolve in this area with new AI techniques and improvements.

7 Video Players That Support AI-Enhanced HEVC Playback in 2024 - MX Player Pro Adds Tensor Processing For Mobile HEVC Playback

MX Player Pro has recently incorporated tensor processing to enhance its ability to handle HEVC video playback on mobile devices. This addition is intended to make viewing high-resolution videos smoother and more efficient, especially on phones and tablets with multiple processing cores. It's designed to work well with modern video and audio codecs, including support for 10-bit video playback. Some users have seen significant performance boosts, with reports of up to a 70% improvement in decoding speeds.

Despite these improvements, there are still challenges. Some users have reported trouble playing HEVC files directly, likely due to limitations in the devices' hardware decoding capabilities. It's a reminder that while software can improve, hardware can sometimes be the bottleneck. Even with these issues, MX Player Pro is notable for maintaining a lightweight design that doesn't impact playback of large, demanding video files. It handles 4K and even 8K content with apparent ease. However, some have also reported difficulties playing back offline HEVC movies, potentially due to either device or software-related complications.

While the introduction of tensor processing is a positive step, it appears MX Player Pro may still need further refinements to fully utilize this feature and provide consistently smooth performance across different devices and file types. The potential is there for significant improvements in mobile HEVC playback, but it appears the journey toward a truly seamless experience might require further development.

MX Player Pro, in its 2024 iteration, has incorporated tensor processing for HEVC (H.265) playback on mobile devices. This shift to specialized hardware for decoding is interesting because it can potentially lead to more efficient energy use compared to traditional CPU-based approaches. The player's optimized for 10-bit video playback and supports various modern audio and video codecs. They've implemented something called Hybrid Hardware Acceleration to speed up video decoding which, based on some user reports, can improve decoding speeds by as much as 70% on devices with multi-core chipsets.

While it handles HEVC formats, some users have reported hiccups when trying to play HEVC files directly, particularly when relying on hardware decoding. This suggests potential compatibility issues, possibly linked to variations in device hardware. Despite this, MX Player Pro retains a lightweight design yet can manage large video files without obvious performance issues, and it easily plays back content in 4K and 8K resolutions. However, there are reports of problems specifically with offline HEVC movie playback, suggesting possible issues that could stem from either device limitations or specific characteristics of the software itself.

It's worth remembering that MX Player Pro isn't alone in the AI-enhanced HEVC landscape of 2024; other players have emerged with similar features. And it seems that even with more players supporting the format, there are still potential difficulties that can occur for users, indicating a need for further optimization and standardized codec support across devices. It's an area that warrants close observation as HEVC continues to be more common. This is a fascinating area, though there are some apparent inconsistencies when decoding certain content which might be a hurdle in widespread adoption. It will be interesting to see how the situation develops going forward.