1 citations · 3 across the 13 of their papers we have counts for
14 papers
PAWBench: How Far Are We from Probabilistically Aligned World Modeling?
Yuandong Pu, Le Zhuo, Sayak Paul +11
Recent video generation models are increasingly framed as world models. Many physical processes can unfold in more than one valid way. Therefore, a world model should reproduce not…
Open Evaluation Agent: Efficient and Promptable Evaluation of Visual Generative Models
Shulin Tian, Ziqi Huang, Fan Zhang +3
Recent advances in visual generative models have enabled high-quality image and video generation, but evaluating these models often demands sampling hundreds or thousands of images…
AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation
Haoyue Tan, Shengnan Wang, Yulin Qiao +5
Video diffusion transformers (DiTs) suffer from prohibitive inference latency due to quadratic attention complexity. Existing sparse attention methods either overlook semantic simi…
LongVie 2: Multimodal Controllable Ultra-Long Video World Model
Jianxiong Gao, Zhaoxi Chen, Xian Liu +7
Building video world models upon pretrained video generation systems represents an important yet challenging step toward general spatiotemporal intelligence. A world model should p…
Uni-MMMU: A Massive Multi-discipline Multimodal Unified Benchmark
Kai Zou, Ziqi Huang, Yuhao Dong +7
Unified multimodal models aim to jointly enable visual understanding and generation, yet current benchmarks rarely examine their true integration. Existing evaluations either treat…
LongVie: Multimodal-Guided Controllable Ultra-Long Video Generation
Jianxiong Gao, Zhaoxi Chen, Xian Liu +5
Controllable ultra-long video generation is a fundamental yet challenging task. Although existing methods are effective for short clips, they struggle to scale due to issues such a…
Dual-Expert Consistency Model for Efficient and High-Quality Video Generation
Zhengyao Lv, Chenyang Si, Tianlin Pan +4
Diffusion Models have achieved remarkable results in video synthesis but require iterative denoising steps, leading to substantial computational overhead. Consistency Models have m…
VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness
Dian Zheng, Ziqi Huang, Hongbo Liu +9
Video generation has advanced significantly, evolving from producing unrealistic outputs to generating videos that appear visually convincing and temporally coherent. To evaluate t…
RepVideo: Rethinking Cross-Layer Representation for Video Generation
Chenyang Si, Weichen Fan, Zhengyao Lv +3
Video generation has achieved remarkable progress with the introduction of diffusion models, which have significantly improved the quality of generated videos. However, recent rese…
Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models
Weichen Fan, Chenyang Si, Junhao Song +16
We present Vchitect-2.0, a parallel transformer architecture designed to scale up video diffusion models for large-scale text-to-video generation. The overall Vchitect-2.0 system h…
Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models
Fan Zhang, Shulin Tian, Ziqi Huang +2
Recent advancements in visual generative models have enabled high-quality image and video generation, opening diverse applications. However, evaluating these models often demands s…
VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models
Ziqi Huang, Fan Zhang, Xiaojie Xu +14
Video generation has witnessed significant advancements, yet evaluating these models remains a challenge. A comprehensive evaluation benchmark for video generation is indispensable…
FasterCache: Training-Free Video Diffusion Model Acceleration with High Quality
Zhengyao Lv, Chenyang Si, Junhao Song +4
In this paper, we present \textbf{\textit{FasterCache}}, a novel training-free strategy designed to accelerate the inference of video diffusion models with high-quality generation.…
DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes
Hengwei Bian, Lingdong Kong, Haozhe Xie +3
Urban scene generation has been developing rapidly recently. However, existing methods primarily focus on generating static and single-frame scenes, overlooking the inherently dyna…