1 citations · 2 across the 8 of their papers we have counts for
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Visual Token Codec: Unleashing Spatial Redundancy for ViT Feature Coding
Donghui Feng, Fengxi Zhang, Changsheng Gao +6
Distributed deployment of large vision foundation models often partitions a ViT backbone and exchanges intermediate token features between computing nodes, making efficient feature…
S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression
Yunuo Chen, Qian Li, Bing He +6
Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of…
Linear Attention Modeling for Learned Image Compression
Donghui Feng, Zhengxue Cheng, Shen Wang +4
Recent years, learned image compression has made tremendous progress to achieve impressive coding efficiency. Its coding gain mainly comes from non-linear neural network-based tran…
CMC-Bench: Towards a New Paradigm of Visual Signal Compression
Chunyi Li, Xiele Wu, Haoning Wu +7
Ultra-low bitrate image compression is a challenging and demanding topic. With the development of Large Multimodal Models (LMMs), a Cross Modality Compression (CMC) paradigm of Ima…
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
Chunyi Li, Guo Lu, Donghui Feng +6
With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic. However, existing compression algorithms must sa…