87 citations · 366 across the 23 of their papers we have counts for
8 papers · 1 filter
Searching the Search Space of Vision Transformer
Minghao Chen, Kan Wu, Bolin Ni +5
Vision Transformer has shown great visual representation power in substantial vision tasks such as recognition and detection, and thus been attracting fast-growing efforts on manua…
Rethinking and Improving Relative Position Encoding for Vision Transformer
Kan Wu, Houwen Peng, Minghao Chen +2
Relative position encoding (RPE) is important for transformer to capture sequence ordering of input tokens. General efficacy has been proven in natural language processing. However…
AutoFormer: Searching Transformers for Visual Recognition
Minghao Chen, Houwen Peng, Jianlong Fu +1
Recently, pure transformer-based models have shown great potentials for vision tasks such as image classification and detection. However, the design of transformer networks is chal…
CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
Chulin Xie, Minghao Chen, Pin-Yu Chen +1
Federated Learning (FL) as a distributed learning paradigm that aggregates information from diverse clients to train a shared global model, has demonstrated great success. However,…
Salient Object Ranking with Position-Preserved Attention
Hao Fang, Daoxin Zhang, Yi Zhang +5
Instance segmentation can detect where the objects are in an image, but hard to understand the relationship between them. We pay attention to a typical relationship, relative salie…
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking
Minghao Chen, Houwen Peng, Jianlong Fu +1
Despite remarkable progress achieved, most neural architecture search (NAS) methods focus on searching for one single accurate and robust architecture. To further build models with…