2.8k citations · 3.2k across the 23 of their papers we have counts for
11 papers · 1 filter
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…
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…
Regressive Domain Adaptation for Unsupervised Keypoint Detection
Junguang Jiang, Yifei Ji, Ximei Wang +3
Domain adaptation (DA) aims at transferring knowledge from a labeled source domain to an unlabeled target domain. Though many DA theories and algorithms have been proposed, most of…
Learning to Transfer Examples for Partial Domain Adaptation
Zhangjie Cao, Kaichao You, Mingsheng Long +2
Domain adaptation is critical for learning in new and unseen environments. With domain adversarial training, deep networks can learn disentangled and transferable features that eff…
Spatiotemporal Pyramid Network for Video Action Recognition
Yunbo Wang, Mingsheng Long, Jianmin Wang +1
Two-stream convolutional networks have shown strong performance in video action recognition tasks. The key idea is to learn spatiotemporal features by fusing convolutional networks…
Deep Triplet Quantization
Bin Liu, Yue Cao, Mingsheng Long +2
Deep hashing establishes efficient and effective image retrieval by end-to-end learning of deep representations and hash codes from similarity data. We present a compact coding sol…