2 citations · 2 across the 8 of their papers we have counts for
7 papers · 1 filter
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…
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…
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…
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…
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…
Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object Detection
Lv Tang, Peng-Tao Jiang, Zhihao Shen +3
In this paper, we introduce a novel multimodal camo-perceptive framework (MMCPF) aimed at handling zero-shot Camouflaged Object Detection (COD) by leveraging the powerful capabilit…
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…