1 citations · 1 across the 11 of their papers we have counts for
15 papers
Proof of the Penrose Conjecture for Maximally Parameterized Initial Data Sets
Hubert Bray, Tuan Dolmen, Marcus Khuri +1
We prove the spacetime Penrose inequality for asymptotically flat initial data sets in all dimensions , under the dominant energy condition, for data admitting…
ParallelWorld: Test-Time Scaling for Agentic Embodied Reasoning
Min Chen, Shengjun Zhang, Yuxin Li +4
Embodied AI has emerged as a key paradigm for autonomous systems operating in complex physical environments. While end-to-end models have established strong local capabilities for…
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…
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…
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…
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…
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…
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…
E-GRPO: High Entropy Steps Drive Effective Reinforcement Learning for Flow Models
Shengjun Zhang, Zhang Zhang, Chensheng Dai +1
Recent reinforcement learning has enhanced the flow matching models on human preference alignment. While stochastic sampling enables the exploration of denoising directions, existi…
ScenePainter: Semantically Consistent Perpetual 3D Scene Generation with Concept Relation Alignment
Chong Xia, Shengjun Zhang, Fangfu Liu +3
Perpetual 3D scene generation aims to produce long-range and coherent 3D view sequences, which is applicable for long-term video synthesis and 3D scene reconstruction. Existing met…
Learning Efficient and Generalizable Human Representation with Human Gaussian Model
Yifan Liu, Shengjun Zhang, Chensheng Dai +4
Modeling animatable human avatars from videos is a long-standing and challenging problem. While conventional methods require per-instance optimization, recent feed-forward methods…
Scene Splatter: Momentum 3D Scene Generation from Single Image with Video Diffusion Model
Shengjun Zhang, Jinzhao Li, Xin Fei +2
In this paper, we propose Scene Splatter, a momentum-based paradigm for video diffusion to generate generic scenes from single image. Existing methods, which employ video generatio…
Gaussian Graph Network: Learning Efficient and Generalizable Gaussian Representations from Multi-view Images
Shengjun Zhang, Xin Fei, Fangfu Liu +2
3D Gaussian Splatting (3DGS) has demonstrated impressive novel view synthesis performance. While conventional methods require per-scene optimization, more recently several feed-for…
Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion
Fangfu Liu, Hanyang Wang, Shunyu Yao +3
In recent years, there has been rapid development in 3D generation models, opening up new possibilities for applications such as simulating the dynamic movements of 3D objects and…
GeoAuxNet: Towards Universal 3D Representation Learning for Multi-sensor Point Clouds
Shengjun Zhang, Xin Fei, Yueqi Duan
Point clouds captured by different sensors such as RGB-D cameras and LiDAR possess non-negligible domain gaps. Most existing methods design different network architectures and trai…