500 citations · 2k across the 65 of their papers we have counts for
7 papers · 1 filter
iVideoGPT: Interactive VideoGPTs are Scalable World Models
Jialong Wu, Shaofeng Yin, Ningya Feng +4
World models empower model-based agents to interactively explore, reason, and plan within imagined environments for real-world decision-making. However, the high demand for interac…
Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning
Jialong Wu, Haoyu Ma, Chaoyi Deng +1
Unsupervised pre-training methods utilizing large and diverse datasets have achieved tremendous success across a range of domains. Recent work has investigated such unsupervised pr…
MetaSets: Meta-Learning on Point Sets for Generalizable Representations
Chao Huang, Zhangjie Cao, Yunbo Wang +2
Deep learning techniques for point clouds have achieved strong performance on a range of 3D vision tasks. However, it is costly to annotate large-scale point sets, making it critic…
Continual Predictive Learning from Videos
Geng Chen, Wendong Zhang, Han Lu +4
Predictive learning ideally builds the world model of physical processes in one or more given environments. Typical setups assume that we can collect data from all environments at…
Decoupled Adaptation for Cross-Domain Object Detection
Junguang Jiang, Baixu Chen, Jianmin Wang +1
Cross-domain object detection is more challenging than object classification since multiple objects exist in an image and the location of each object is unknown in the unlabeled ta…
Open Domain Generalization with Domain-Augmented Meta-Learning
Yang Shu, Zhangjie Cao, Chenyu Wang +2
Leveraging datasets available to learn a model with high generalization ability to unseen domains is important for computer vision, especially when the unseen domain's annotated da…
VideoDG: Generalizing Temporal Relations in Videos to Novel Domains
Zhiyu Yao, Yunbo Wang, Jianmin Wang +2
This paper introduces video domain generalization where most video classification networks degenerate due to the lack of exposure to the target domains of divergent distributions.…