10 papers
WeThink: Toward General-purpose Vision-Language Reasoning via Reinforcement Learning
Jie Yang, Feipeng Ma, Zitian Wang +4
Building on the success of text-based reasoning models like DeepSeek-R1, extending these capabilities to multimodal reasoning holds great promise. While recent works have attempted…
Unlock the Power of Unlabeled Data in Language Driving Model
Chaoqun Wang, Jie Yang, Xiaobin Hong +1
Recent Vision-based Large Language Models~(VisionLLMs) for autonomous driving have seen rapid advancements. However, such promotion is extremely dependent on large-scale high-quali…
Semantic-Supervised Spatial-Temporal Fusion for LiDAR-based 3D Object Detection
Chaoqun Wang, Xiaobin Hong, Wenzhong Li +1
LiDAR-based 3D object detection presents significant challenges due to the inherent sparsity of LiDAR points. A common solution involves long-term temporal LiDAR data to densify th…
Motion-X++: A Large-Scale Multimodal 3D Whole-body Human Motion Dataset
Yuhong Zhang, Jing Lin, Ailing Zeng +7
In this paper, we introduce Motion-X++, a large-scale multimodal 3D expressive whole-body human motion dataset. Existing motion datasets predominantly capture body-only poses, lack…
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model
Shunlin Lu, Jingbo Wang, Zeyu Lu +6
The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation re…
KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension
Jie Yang, Wang Zeng, Sheng Jin +4
Recent advancements in Multimodal Large Language Models (MLLMs) have greatly improved their abilities in image understanding. However, these models often struggle with grasping pix…