11 papers · 1 filter
Harvest Video Foundation Models via Efficient Post-Pretraining
Yizhuo Li, Kunchang Li, Yinan He +5
Building video-language foundation models is costly and difficult due to the redundant nature of video data and the lack of high-quality video-language datasets. In this paper, we…
Efficient High-Resolution Visual Representation Learning with State Space Model for Human Pose Estimation
Hao Zhang, Yongqiang Ma, Wenqi Shao +3
Capturing long-range dependencies while preserving high-resolution visual representations is crucial for dense prediction tasks such as human pose estimation. Vision Transformers (…
GUIOdyssey: A Comprehensive Dataset for Cross-App GUI Navigation on Mobile Devices
Quanfeng Lu, Wenqi Shao, Zitao Liu +7
Autonomous Graphical User Interface (GUI) navigation agents can enhance user experience in communication, entertainment, and productivity by streamlining workflows and reducing man…
SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations
Xiangchao Yan, Runjian Chen, Bo Zhang +11
Annotating 3D LiDAR point clouds for perception tasks is fundamental for many applications e.g., autonomous driving, yet it still remains notoriously labor-intensive. Pretraining-f…
MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Fanqing Meng, Lingxiao Du, Zongkai Liu +12
DeepSeek R1, and o1 have demonstrated powerful reasoning capabilities in the text domain through stable large-scale reinforcement learning. To enable broader applications, some wor…
SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement
Yuqi Lin, Hengjia Li, Wenqi Shao +5
In this paper, we explore a principal way to enhance the quality of widely pre-existing coarse masks, enabling them to serve as reliable training data for segmentation models to re…