93 citations · 476 across the 42 of their papers we have counts for
12 papers · 1 filter
The Overlooked Classifier in Human-Object Interaction Recognition
Ying Jin, Yinpeng Chen, Lijuan Wang +5
Human-Object Interaction (HOI) recognition is challenging due to two factors: (1) significant imbalance across classes and (2) requiring multiple labels per image. This paper shows…
Improving Vision Transformers for Incremental Learning
Pei Yu, Yinpeng Chen, Ying Jin +1
This paper proposes a working recipe of using Vision Transformer (ViT) in class incremental learning. Although this recipe only combines existing techniques, developing the combina…
BEVT: BERT Pretraining of Video Transformers
Rui Wang, Dongdong Chen, Zuxuan Wu +6
This paper studies the BERT pretraining of video transformers. It is a straightforward but worth-studying extension given the recent success from BERT pretraining of image transfor…
Unsupervised Finetuning
Suichan Li, Dongdong Chen, Yinpeng Chen +5
This paper studies "unsupervised finetuning", the symmetrical problem of the well-known "supervised finetuning". Given a pretrained model and small-scale unlabeled target data, uns…
MicroNet: Improving Image Recognition with Extremely Low FLOPs
Yunsheng Li, Yinpeng Chen, Xiyang Dai +6
This paper aims at addressing the problem of substantial performance degradation at extremely low computational cost (e.g. 5M FLOPs on ImageNet classification). We found that two f…
Mobile-Former: Bridging MobileNet and Transformer
Yinpeng Chen, Xiyang Dai, Dongdong Chen +4
We present Mobile-Former, a parallel design of MobileNet and transformer with a two-way bridge in between. This structure leverages the advantages of MobileNet at local processing…
Is Object Detection Necessary for Human-Object Interaction Recognition?
Ying Jin, Yinpeng Chen, Lijuan Wang +4
This paper revisits human-object interaction (HOI) recognition at image level without using supervisions of object location and human pose. We name it detection-free HOI recognitio…
Improve Unsupervised Pretraining for Few-label Transfer
Suichan Li, Dongdong Chen, Yinpeng Chen +5
Unsupervised pretraining has achieved great success and many recent works have shown unsupervised pretraining can achieve comparable or even slightly better transfer performance th…
Dynamic Head: Unifying Object Detection Heads with Attentions
Xiyang Dai, Yinpeng Chen, Bin Xiao +4
The complex nature of combining localization and classification in object detection has resulted in the flourished development of methods. Previous works tried to improve the perfo…
Dynamic Transfer for Multi-Source Domain Adaptation
Yunsheng Li, Lu Yuan, Yinpeng Chen +2
Recent works of multi-source domain adaptation focus on learning a domain-agnostic model, of which the parameters are static. However, such a static model is difficult to handle co…
Revisiting Dynamic Convolution via Matrix Decomposition
Yunsheng Li, Yinpeng Chen, Xiyang Dai +7
Recent research in dynamic convolution shows substantial performance boost for efficient CNNs, due to the adaptive aggregation of K static convolution kernels. It has two limitatio…
Stronger NAS with Weaker Predictors
Junru Wu, Xiyang Dai, Dongdong Chen +7
Neural Architecture Search (NAS) often trains and evaluates a large number of architectures. Recent predictor-based NAS approaches attempt to alleviate such heavy computation costs…