1 citations · 1 across the 7 of their papers we have counts for
9 papers
Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors
Yunuo Chen, Jingnan Gao, Bing He +6
Pretrained diffusion models provide powerful generative priors for extreme image compression, but their stochastic, iterative generation processes are not designed to decode compre…
CompactSplat: Spatially Adaptive Gaussian Distribution for Feedforward Scene Reconstruction
Bing He, Jingnan Gao, Yunuo Chen +4
Reconstructing 3D scenes from sparse views without per-scene optimization remains highly challenging, especially for recovering accurate geometry and fine textures. While recent fe…
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…
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…
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…
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…
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…
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…
Implicit-explicit Integrated Representations for Multi-view Video Compression
Chen Zhu, Guo Lu, Bing He +2
With the increasing consumption of 3D displays and virtual reality, multi-view video has become a promising format. However, its high resolution and multi-camera shooting result in…