activity
20192022
most citedAbstract Reasoning with Distracting Features

30 citations · 101 across the 14 of their papers we have counts for

collaborators

15 papers

cs.LG2022

Neural Dependencies Emerging from Learning Massive Categories

Ruili Feng, Kecheng Zheng, Kai Zhu +7

This work presents two astonishing findings on neural networks learned for large-scale image classification. 1) Given a well-trained model, the logits predicted for some category c…

cs.LG2022

Principled Knowledge Extrapolation with GANs

Ruili Feng, Jie Xiao, Kecheng Zheng +4

Human can extrapolate well, generalize daily knowledge into unseen scenarios, raise and answer counterfactual questions. To imitate this ability via generative models, previous wor…

cs.CV20225 cited

FAMLP: A Frequency-Aware MLP-Like Architecture For Domain Generalization

Kecheng Zheng, Yang Cao, Kai Zhu +2

MLP-like models built entirely upon multi-layer perceptrons have recently been revisited, exhibiting the comparable performance with transformers. It is one of most promising archi…

cs.CV2022

Modality-Adaptive Mixup and Invariant Decomposition for RGB-Infrared Person Re-Identification

Zhipeng Huang, Jiawei Liu, Liang Li +2

RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrar…

cs.CV20224 cited

Debiased Batch Normalization via Gaussian Process for Generalizable Person Re-Identification

Jiawei Liu, Zhipeng Huang, Liang Li +2

Generalizable person re-identification aims to learn a model with only several labeled source domains that can perform well on unseen domains. Without access to the unseen domain,…

cs.CV20219 cited

Semi-Supervised Domain Generalizable Person Re-Identification

Lingxiao He, Wu Liu, Jian Liang +4

Existing person re-identification (re-id) methods are stuck when deployed to a new unseen scenario despite the success in cross-camera person matching. Recent efforts have been sub…