7 citations · 15 across the 6 of their papers we have counts for
6 papers
Long-Tailed Learning as Multi-Objective Optimization
Weiqi Li, Fan Lyu, Fanhua Shang +2
Real-world data is extremely imbalanced and presents a long-tailed distribution, resulting in models that are biased towards classes with sufficient samples and perform poorly on r…
Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation
Tingliang Feng, Hao Shi, Xueyang Liu +4
Many methods of semantic image segmentation have borrowed the success of open compound domain adaptation. They minimize the style gap between the images of source and target domain…
Learning Restoration is Not Enough: Transfering Identical Mapping for Single-Image Shadow Removal
Xiaoguang Li, Qing Guo, Pingping Cai +3
Shadow removal is to restore shadow regions to their shadow-free counterparts while leaving non-shadow regions unchanged. State-of-the-art shadow removal methods train deep neural…
ESimCSE Unsupervised Contrastive Learning Jointly with UDA Semi-Supervised Learning for Large Label System Text Classification Mode
Ruan Lu, Zhou HangCheng, Ran Meng +4
The challenges faced by text classification with large tag systems in natural language processing tasks include multiple tag systems, uneven data distribution, and high noise. To a…
Continuous Sign Language Recognition with Correlation Network
Lianyu Hu, Liqing Gao, Zekang Liu +1
Human body trajectories are a salient cue to identify actions in the video. Such body trajectories are mainly conveyed by hands and face across consecutive frames in sign language.…
Temporal Lift Pooling for Continuous Sign Language Recognition
Lianyu Hu, Liqing Gao, Zekang Liu +1
Pooling methods are necessities for modern neural networks for increasing receptive fields and lowering down computational costs. However, commonly used hand-crafted pooling approa…