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Contrastive Knowledge Amalgamation for Unsupervised Image Classification
Shangde Gao, Yichao Fu, Ke Liu +1
Knowledge amalgamation (KA) aims to learn a compact student model to handle the joint objective from multiple teacher models that are are specialized for their own tasks respective…
Pose-disentangled Contrastive Learning for Self-supervised Facial Representation
Yuanyuan Liu, Wenbin Wang, Yibing Zhan +3
Self-supervised facial representation has recently attracted increasing attention due to its ability to perform face understanding without relying on large-scale annotated datasets…
Learning from Pixel-Level Noisy Label : A New Perspective for Light Field Saliency Detection
Mingtao Feng, Kendong Liu, Liang Zhang +3
Saliency detection with light field images is becoming attractive given the abundant cues available, however, this comes at the expense of large-scale pixel level annotated data wh…
CTM: Collaborative Temporal Modeling for Action Recognition
Qian Liu, Tao Wang, Jie Liu +3
With the rapid development of digital multimedia, video understanding has become an important field. For action recognition, temporal dimension plays an important role, and this is…
iqiyi Submission to ActivityNet Challenge 2019 Kinetics-700 challenge: Hierarchical Group-wise Attention
Qian Liu, Dongyang Cai, Jie Liu +2
In this report, the method for the iqiyi submission to the task of ActivityNet 2019 Kinetics-700 challenge is described. Three models are involved in the model ensemble stage: TSN,…
Learning to Recognize Pedestrian Attribute
Yubin Deng, Ping Luo, Chen Change Loy +1
Learning to recognize pedestrian attributes at far distance is a challenging problem in visual surveillance since face and body close-shots are hardly available; instead, only far-…