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20232026
most citedUAR-NVC: A Unified AutoRegressive Framework for Memory-Efficient Neural Video Compression

2 citations · 2 across the 10 of their papers we have counts for

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cs.CV2026

DROSR: Degradation-Disentangled Representation for Real-World Omnidirectional Image Super-Resolution

Hongyu An, Xinfeng Zhang, Xu Fan +3

With the growing demand for immersive visual experiences, high-quality omnidirectional images (ODIs) have become increasingly important. However, limitations in imaging devices and…

cs.CV2026

Video Compression with Hierarchical Temporal Neural Representation

Jun Zhu, Xinfeng Zhang, Lv Tang +3

Video compression has recently benefited from implicit neural representations (INRs), which model videos as continuous functions. INRs offer compact storage and flexible reconstruc…

cs.CV2026

Frequency-aware Neural Representation for Videos

Jun Zhu, Xinfeng Zhang, Lv Tang +3

Implicit Neural Representations (INRs) have emerged as a promising paradigm for video compression. However, existing INR-based frameworks typically suffer from inherent spectral bi…

cs.CV2025

MSNeRV: Neural Video Representation with Multi-Scale Feature Fusion

Jun Zhu, Xinfeng Zhang, Lv Tang +1

Implicit Neural representations (INRs) have emerged as a promising approach for video compression, and have achieved comparable performance to the state-of-the-art codecs such as H…

cs.CV2025★ 2 cited

UAR-NVC: A Unified AutoRegressive Framework for Memory-Efficient Neural Video Compression

Jia Wang, Xinfeng Zhang, Gai Zhang +3

Implicit Neural Representations (INRs) have demonstrated significant potential in video compression by representing videos as neural networks. However, as the number of frames incr…

cs.CV2025

CANeRV: Content Adaptive Neural Representation for Video Compression

Lv Tang, Jun Zhu, Xinfeng Zhang +3

Recent advances in video compression introduce implicit neural representation (INR) based methods, which effectively capture global dependencies and characteristics of entire video…

cs.CV2025

Spatial Degradation-Aware and Temporal Consistent Diffusion Model for Compressed Video Super-Resolution

Hongyu An, Xinfeng Zhang, Shijie Zhao +2

Due to storage and bandwidth limitations, videos transmitted over the Internet often exhibit low quality, characterized by low-resolution and compression artifacts. Although video…

cs.CV2024

Spatio-Temporal Distortion Aware Omnidirectional Video Super-Resolution

Hongyu An, Xinfeng Zhang, Shijie Zhao +2

Omnidirectional videos (ODVs) provide an immersive visual experience by capturing the 360° scene. With the rapid advancements in virtual/augmented reality, metaverse, and generativ…

cs.CV2023

Scene Matters: Model-based Deep Video Compression

Lv Tang, Xinfeng Zhang, Gai Zhang +1

Video compression has always been a popular research area, where many traditional and deep video compression methods have been proposed. These methods typically rely on signal pred…