While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing methods attempt to understand the world by internalizing diverse world knowledge, yet constrained by computational overhead or dimensionality alignment, their learning proc...
Bo Tan, Xiang-Dong Zhang, Yan Xia et al.· 0 citations
3D instance segmentation requires representations that are both geometrically structured and semantically discriminative. Pure 3D encoders model spatial structure well but often lack strong appearance semantics, while directly lifting 2D priors into 3D by concatenation injects rich semantics without ensuring that they...
Generating LiDAR point clouds from multi-view camera images is a valuable task with applications in controllable data synthesis, cross-modal simulation and various perception tasks. However, most existing methods are not specifically designed for this task, and the quality of their generated LiDAR remains limited. More...
Si-Zhuo Zhou, Xiao-Song Jia, Fan-Rui Zhang et al.· 0 citations
TRWORLDBENCH is introduced, a benchmark for evaluating embodied world models through synchronized head, left-wrist, and right-wrist videos and uses 19 metrics to assess tri-view consistency, task alignment, physical and 3D coherence, motion quality, temporal consistency, and visual quality.
Xuan-Yi Liu, Hao-Feng Wang, Rui-Qi Li et al.· 0 citations
A role-aware signal that groups entities into agents, controlled objects, passive objects, and background, so that different physical roles can be modeled more clearly is introduced, and a modality-decoupled denoising strategy, where the visual and auxiliary channels are assigned independent noise levels, is proposed.
Guangting Zheng, Haojing Chen, Hao Li et al.· 2 citations
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