2 citations · 2 across the 3 of their papers we have counts for
5 papers
Vector-Decomposed Disentanglement for Domain-Invariant Object Detection
Aming Wu, Rui Liu, Yahong Han +2
To improve the generalization of detectors, for domain adaptive object detection (DAOD), recent advances mainly explore aligning feature-level distributions between the source and…
Domain-Smoothing Network for Zero-Shot Sketch-Based Image Retrieval
Zhipeng Wang, Hao Wang, Jiexi Yan +2
Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is a novel cross-modal retrieval task, where abstract sketches are used as queries to retrieve natural images under zero-shot scena…
Universal-Prototype Enhancing for Few-Shot Object Detection
Aming Wu, Yahong Han, Linchao Zhu +1
Few-shot object detection (FSOD) aims to strengthen the performance of novel object detection with few labeled samples. To alleviate the constraint of few samples, enhancing the ge…
Hierarchical Memory Decoding for Video Captioning
Aming Wu, Yahong Han
Recent advances of video captioning often employ a recurrent neural network (RNN) as the decoder. However, RNN is prone to diluting long-term information. Recent works have demonst…
Instance-Invariant Domain Adaptive Object Detection via Progressive Disentanglement
Aming Wu, Yahong Han, Linchao Zhu +1
Most state-of-the-art methods of object detection suffer from poor generalization ability when the training and test data are from different domains, e.g., with different styles. T…