1 citations · 1 across the 3 of their papers we have counts for
5 papers
Atomic-WAM: Execution-Grounded Atomic-Motion Reasoning for World Action Models
Shijun Shi, Zhe Liu, Zhi Hou +5
World Action Models (WAMs) typically adapt video foundation models to robotic control through joint video and action prediction. However, task-level instructions may leave the next…
PhysBrain 1.5: From Vision-Language Models to Physical Foundation Models
DeepCybo Team, Yu Bin, Haipeng Cao +51
We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the physical loop of observation,…
RTGen: Generating Region-Text Pairs for Open-Vocabulary Object Detection
Fangyi Chen, Han Zhang, Zhantao Yang +3
Open-vocabulary object detection (OVD) requires solid modeling of the region-semantic relationship, which could be learned from massive region-text pairs. However, such data is lim…
Slight Corruption in Pre-training Data Makes Better Diffusion Models
Hao Chen, Yujin Han, Diganta Misra +6
Diffusion models (DMs) have shown remarkable capabilities in generating realistic high-quality images, audios, and videos. They benefit significantly from extensive pre-training on…
Completing Visual Objects via Bridging Generation and Segmentation
Xiang Li, Yinpeng Chen, Chung-Ching Lin +6
This paper presents a novel approach to object completion, with the primary goal of reconstructing a complete object from its partially visible components. Our method, named MaskCo…