Learning-based video compression has recently achieved competitive rate-distortion performance compared to conventional video codecs. However, most existing methods rely on non-invertible analysis-synthesis transforms, with reconstruction quality subject to both quantization and transform approximation errors. This limitation becomes particularly restrictive at higher quality points, where quantization errors are small and transform-induced distortion dominates. To address this, we propose InnVC, an Invertible neural network based Video Codec for wide-range and high-fidelity compression. The core idea is to preserve an invertible main transform path prior to quantization, while injecting content-adaptive context through a compact implicit conditioning field. This decouples strongly correlated video content from harder-to-model fine details, allowing different components to specialize in complementary reconstruction tasks for more efficient compression. To further improve compressibility, we introduce a scheduled masking strategy that progressively concentrates informative content into fewer latent channels for more effective entropy coding. Experiments on the UVG and MCL-JCV benchmarks show that InnVC achieves strong compression performance over a broad quality range, being particularly effective in the high-quality regime, yielding BD-rate reductions of 21.66% in PSNR and 46.06% in MS-SSIM relative to x265 on UVG. To the best of our knowledge, InnVC is the first neural video codec covers operating poins from low bitrate to high fidelity within a single architecture scale, spanning more than 20 dB in PSNR.

翻译：基于学习的视频压缩近期在率失真性能上已与传统视频编解码器相当。然而，现有方法大多采用非可逆的分析-合成变换，其重建质量同时受量化误差与变换近似误差影响。这种局限性在高质量点尤为突出——当量化误差较小时，变换引起的失真占据主导地位。为解决该问题，我们提出InnVC——一种基于可逆神经网络的视频编解码器，适用于宽范围高保真压缩。核心思想是在量化前保留可逆主变换路径，同时通过紧凑的隐式条件场注入内容自适应上下文。该设计将强相关视频内容与难以建模的精细细节解耦，使不同组件专注于互补重建任务，从而提升压缩效率。为进一步增强可压缩性，我们引入调度掩蔽策略，逐步将信息内容集中到更少的潜通道中，以实现更高效的熵编码。在UVG与MCL-JCV基准上的实验表明，InnVC在宽质量范围内均表现出强劲压缩性能，尤其在高保真区间效果显著——相较于x265，在UVG上实现PSNR BD率降低21.66%，MS-SSIM BD率降低46.06%。据我们所知，InnVC是首个在单一架构尺度下覆盖从低比特率到高保真操作点（PSNR跨度超过20 dB）的神经视频编解码器。