2.8k citations · 7.4k across the 41 of their papers we have counts for
13 papers · 1 filter
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…
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions
Haixu Wu, Zhiyu Yao, Jianmin Wang +1
This paper tackles video prediction from a new dimension of predicting spacetime-varying motions that are incessantly changing across both space and time. Prior methods mainly capt…
Negative Margin Matters: Understanding Margin in Few-shot Classification
Bin Liu, Yue Cao, Yutong Lin +4
This paper introduces a negative margin loss to metric learning based few-shot learning methods. The negative margin loss significantly outperforms regular softmax loss, and achiev…
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…
Multi-Task Learning of Generalizable Representations for Video Action Recognition
Zhiyu Yao, Yunbo Wang, Mingsheng Long +3
In classic video action recognition, labels may not contain enough information about the diverse video appearance and dynamics, thus, existing models that are trained under the sta…
Multi-Adversarial Domain Adaptation
Zhongyi Pei, Zhangjie Cao, Mingsheng Long +1
Recent advances in deep domain adaptation reveal that adversarial learning can be embedded into deep networks to learn transferable features that reduce distribution discrepancy be…
Deep Priority Hashing
Zhangjie Cao, Ziping Sun, Mingsheng Long +2
Deep hashing enables image retrieval by end-to-end learning of deep representations and hash codes from training data with pairwise similarity information. Subject to the distribut…
Partial Adversarial Domain Adaptation
Zhangjie Cao, Lijia Ma, Mingsheng Long +1
Domain adversarial learning aligns the feature distributions across the source and target domains in a two-player minimax game. Existing domain adversarial networks generally assum…
Transfer Adversarial Hashing for Hamming Space Retrieval
Zhangjie Cao, Mingsheng Long, Chao Huang +1
Hashing is widely applied to large-scale image retrieval due to the storage and retrieval efficiency. Existing work on deep hashing assumes that the database in the target domain i…
Transitive Hashing Network for Heterogeneous Multimedia Retrieval
Zhangjie Cao, Mingsheng Long, Qiang Yang
Hashing has been widely applied to large-scale multimedia retrieval due to the storage and retrieval efficiency. Cross-modal hashing enables efficient retrieval from database of on…
Correlation Hashing Network for Efficient Cross-Modal Retrieval
Yue Cao, Mingsheng Long, Jianmin Wang +1
Hashing is widely applied to approximate nearest neighbor search for large-scale multimodal retrieval with storage and computation efficiency. Cross-modal hashing improves the qual…