6 papers
Next-Frame Decoding for Ultra-Low-Bitrate Image Compression with Video Diffusion Priors
Yunuo Chen, Chuqin Zhou, Jiangchuan Li +5
We present a novel paradigm for ultra-low-bitrate image compression (ULB-IC) that exploits the ``temporal'' evolution in generative image compression. Specifically, we define an ex…
Adaptive Learned Image Compression with Graph Neural Networks
Yunuo Chen, Bing He, Zezheng Lyu +4
Efficient image compression relies on modeling both local and global redundancy. Most state-of-the-art (SOTA) learned image compression (LIC) methods are based on CNNs or Transform…
Content-Aware Mamba for Learned Image Compression
Yunuo Chen, Zezheng Lyu, Bing He +6
Recent learned image compression (LIC) leverages Mamba-style state-space models (SSMs) for global receptive fields with linear complexity. However, the standard Mamba adopts conten…
SurfSplat: Conquering Feedforward 2D Gaussian Splatting with Surface Continuity Priors
Bing He, Jingnan Gao, Yunuo Chen +5
Reconstructing 3D scenes from sparse images remains a challenging task due to the difficulty of recovering accurate geometry and texture without optimization. Recent approaches lev…
H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting
Bing He, Yunuo Chen, Guo Lu +5
Dynamic scene reconstruction poses a persistent challenge in 3D vision. Deformable 3D Gaussian Splatting has emerged as an effective method for this task, offering real-time render…
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…