8 papers
WorldMem: Long-term Consistent World Simulation with Memory
Zeqi Xiao, Yushi Lan, Yifan Zhou +4
World simulation has gained increasing popularity due to its ability to model virtual environments and predict the consequences of actions. However, the limited temporal context wi…
Trainable Log-linear Sparse Attention for Efficient Diffusion Transformers
Yifan Zhou, Zeqi Xiao, Tianyi Wei +2
Diffusion Transformers (DiTs) set the state of the art in visual generation, yet their quadratic self-attention cost fundamentally limits scaling to long token sequences. Recent To…
Video4Spatial: Towards Visuospatial Intelligence with Context-Guided Video Generation
Zeqi Xiao, Yiwei Zhao, Lingxiao Li +6
We investigate whether video generative models can exhibit visuospatial intelligence, a capability central to human cognition, using only visual data. To this end, we present Video…
Recurrent Autoregressive Diffusion: Global Memory Meets Local Attention
Taiye Chen, Zihan Ding, Anjian Li +4
Recent advancements in video generation has shifted from bidirectional models for short videos to autoregressive ones for ultra long video generation. Previous models, which usuall…
Towards Geometry-Grounded Dense Semantic Matching with VGGT Priors
Songlin Yang, Tianyi Wei, Yushi Lan +3
Semantic matching aims to establish pixel-level correspondences between instances of the same category and represents a fundamental task in computer vision. Existing approaches suf…
Alias-Free Latent Diffusion Models: Improving Fractional Shift Equivariance of Diffusion Latent Space
Yifan Zhou, Zeqi Xiao, Shuai Yang +1
Latent Diffusion Models (LDMs) are known to have an unstable generation process, where even small perturbations or shifts in the input noise can lead to significantly different out…