18 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.CV2023
Calibrated Teacher for Sparsely Annotated Object Detection
Haohan Wang, Liang Liu, Boshen Zhang +6
Fully supervised object detection requires training images in which all instances are annotated. This is actually impractical due to the high labor and time costs and the unavoidab…
cs.CV2023★ 18 cited
Iterative Few-shot Semantic Segmentation from Image Label Text
Haohan Wang, Liang Liu, Wuhao Zhang +5
Few-shot semantic segmentation aims to learn to segment unseen class objects with the guidance of only a few support images. Most previous methods rely on the pixel-level label of…
cs.CV2021★ 1 cited
Enabling the Network to Surf the Internet
Zhuoling Li, Haohan Wang, Tymoteusz Swistek +3
Few-shot learning is challenging due to the limited data and labels. Existing algorithms usually resolve this problem by pre-training the model with a considerable amount of annota…