8 papers
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…
Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration
Yujie Chen, Haotong Qin, Zhang Zhang +3
State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length while effectively capturing long-di…
Beyond Closed-Pool Video Retrieval: A Benchmark and Agent Framework for Real-World Video Search and Moment Localization
Tao Yu, Yujia Yang, Haopeng Jin +17
Traditional video retrieval benchmarks focus on matching precise descriptions to closed video pools, failing to reflect real-world searches characterized by fuzzy, multi-dimensiona…
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…
SportsGPT: An LLM-driven Framework for Interpretable Sports Motion Assessment and Training Guidance
Wenbo Tian, Ruting Lin, Hongxian Zheng +4
Existing intelligent sports analysis systems mainly focus on "scoring and visualization," often lacking automatic performance diagnosis and interpretable training guidance. Recent…