73 citations · 128 across the 7 of their papers we have counts for
9 papers
Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition
Qibin Hou, Cheng-Ze Lu, Ming-Ming Cheng +1
This paper does not attempt to design a state-of-the-art method for visual recognition but investigates a more efficient way to make use of convolutions to encode spatial features.…
Towards Sustainable Self-supervised Learning
Shanghua Gao, Pan Zhou, Ming-Ming Cheng +1
Although increasingly training-expensive, most self-supervised learning (SSL) models have repeatedly been trained from scratch but not fully utilized, since only a few SOTAs are em…
Long-Tailed Class Incremental Learning
Xialei Liu, Yu-Song Hu, Xu-Sheng Cao +3
In class incremental learning (CIL) a model must learn new classes in a sequential manner without forgetting old ones. However, conventional CIL methods consider a balanced distrib…
Towards An End-to-End Framework for Flow-Guided Video Inpainting
Zhen Li, Cheng-Ze Lu, Jianhua Qin +2
Optical flow, which captures motion information across frames, is exploited in recent video inpainting methods through propagating pixels along its trajectories. However, the hand-…
Representation Compensation Networks for Continual Semantic Segmentation
Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu +2
In this work, we study the continual semantic segmentation problem, where the deep neural networks are required to incorporate new classes continually without catastrophic forgetti…
Personalized Image Semantic Segmentation
Yu Zhang, Chang-Bin Zhang, Peng-Tao Jiang +2
Semantic segmentation models trained on public datasets have achieved great success in recent years. However, these models didn't consider the personalization issue of segmentation…