collaborators

11 papers

cs.CV2026

UniqueSplat: View-conditioned 3D Gaussian Splatting for Generalizable 3D Reconstruction

Haixu Song, Xiaoke Yang, Shengjun Zhang +2

In this paper, we propose UniqueSplat, a view-conditioned feed-forward 3D Gaussian Splatting model to reconstruct customized 3D radiance fields for each view query. Existing feed-f…

cs.CV2026

Learning Efficient 4D Gaussian Representations from Monocular Videos with Flow Splatting

Shengjun Zhang, Jinzhao Li, Xin Fei +1

Reconstructing dynamic 3D scenes from monocular videos is challenging due to scene complexity and temporal dynamics. With the advancement of 3D Gaussian Splatting in novel view syn…

cs.CV2026

MBench: A Comprehensive Benchmark on Memory Capability for Video World Models

Shengjun Zhang, Zhang Zhang, Simin Huang +11

Recent advancements in video-based world models have demonstrated an unprecedented ability to synthesize high-fidelity visual sequences. However, a fundamental gap persists between…

cs.CV2026

RhymeFlow: Training-Free Acceleration for Video Generation with Asynchronous Denoising Flow Scheduling

Chensheng Dai, Shengjun Zhang, Yifan Li +3

Video generation models based on Diffusion Transformers (DiTs) have achieved remarkable performance in video synthesis, yet they suffer from high inference latency and computationa…

cs.CV2026

SurfelSplat: Learning Efficient and Generalizable Gaussian Surfel Representations for Sparse-View Surface Reconstruction

Chensheng Dai, Shengjun Zhang, Min Chen +1

3D Gaussian Splatting (3DGS) has demonstrated impressive performance in 3D scene reconstruction. Beyond novel view synthesis, it shows great potential for multi-view surface recons…

cs.CV2026

Revisiting 3D Reconstruction Kernels as Low-Pass Filters

Shengjun Zhang, Min Chen, Yibo Wei +2

3D reconstruction is to recover 3D signals from the sampled discrete 2D pixels, with the goal to converge continuous 3D spaces. In this paper, we revisit 3D reconstruction from the…