16 citations · 16 across the 3 of their papers we have counts for
4 papers
Remedying Target-Domain Astigmatism for Cross-Domain Few-Shot Object Detection
Yongwei Jiang, Yixiong Zou, Yuhua Li +1
Cross-domain few-shot object detection (CD-FSOD) aims to adapt pretrained detectors from a source domain to target domains with limited annotations, suffering from severe domain sh…
WeClick: Weakly-Supervised Video Semantic Segmentation with Click Annotations
Peidong Liu, Zibin He, Xiyu Yan +4
Compared with tedious per-pixel mask annotating, it is much easier to annotate data by clicks, which costs only several seconds for an image. However, applying clicks to learn vide…
Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search
Peidong Liu, Gengwei Zhang, Bochao Wang +4
Designing proper loss functions for vision tasks has been a long-standing research direction to advance the capability of existing models. For object detection, the well-establishe…
Reducing the Annotation Effort for Video Object Segmentation Datasets
Paul Voigtlaender, Lishu Luo, Chun Yuan +2
For further progress in video object segmentation (VOS), larger, more diverse, and more challenging datasets will be necessary. However, densely labeling every frame with pixel mas…