6 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 5 cited
Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation
Chunbo Lang, Binfei Tu, Gong Cheng +1
Few-shot segmentation, which aims to segment unseen-class objects given only a handful of densely labeled samples, has received widespread attention from the community. Existing ap…
cs.CV2022★ 6 cited
Learning Non-target Knowledge for Few-shot Semantic Segmentation
Yuanwei Liu, Nian Liu, Qinglong Cao +3
Existing studies in few-shot semantic segmentation only focus on mining the target object information, however, often are hard to tell ambiguous regions, especially in non-target r…
cs.CV2022
Learning What Not to Segment: A New Perspective on Few-Shot Segmentation
Chunbo Lang, Gong Cheng, Binfei Tu +1
Recently few-shot segmentation (FSS) has been extensively developed. Most previous works strive to achieve generalization through the meta-learning framework derived from classific…