64 citations · 168 across the 32 of their papers we have counts for
4 papers · 1 filter
Dynamic Convolution: Attention over Convolution Kernels
Yinpeng Chen, Xiyang Dai, Mengchen Liu +3
Light-weight convolutional neural networks (CNNs) suffer performance degradation as their low computational budgets constrain both the depth (number of convolution layers) and the…
Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning
Fuxun Yu, Di Wang, Yinpeng Chen +7
Current state-of-the-art object detectors can have significant performance drop when deployed in the wild due to domain gaps with training data. Unsupervised Domain Adaptation (UDA…
Large Scale Incremental Learning
Yue Wu, Yinpeng Chen, Lijuan Wang +4
Modern machine learning suffers from catastrophic forgetting when learning new classes incrementally. The performance dramatically degrades due to the missing data of old classes.…
Rethinking Classification and Localization for Object Detection
Yue Wu, Yinpeng Chen, Lu Yuan +4
Two head structures (i.e. fully connected head and convolution head) have been widely used in R-CNN based detectors for classification and localization tasks. However, there is a l…