3 citations · 4 across the 6 of their papers we have counts for
6 papers
VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models
Xiangdong Zhang, Jiaqi Liao, Shaofeng Zhang +4
Recent advancements in text-to-video (T2V) diffusion models have enabled high-fidelity and realistic video synthesis. However, current T2V models often struggle to generate physica…
Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
Yang Li, Jinpei Guo, Runzhong Wang +2
Diffusion models have recently advanced Combinatorial Optimization (CO) as a powerful backbone for neural solvers. However, their iterative sampling process requiring denoising acr…
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
Xiangdong Zhang, Shaofeng Zhang, Junchi Yan
Masked autoencoder has been widely explored in point cloud self-supervised learning, whereby the point cloud is generally divided into visible and masked parts. These methods typic…
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
Shaofeng Zhang, Jinfa Huang, Qiang Zhou +4
Image outpainting aims to generate the content of an input sub-image beyond its original boundaries. It is an important task in content generation yet remains an open problem for g…
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime
Haoyu Geng, Hang Ruan, Runzhong Wang +4
Predictive combinatorial optimization, where the parameters of combinatorial optimization (CO) are unknown at the decision-making time, is the precise modeling of many real-world a…
On the Evaluation and Refinement of Vision-Language Instruction Tuning Datasets
Ning Liao, Shaofeng Zhang, Renqiu Xia +3
There is an emerging line of research on multimodal instruction tuning, and a line of benchmarks has been proposed for evaluating these models recently. Instead of evaluating the m…