most citedIntermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

37 citations · 48 across the 5 of their papers we have counts for

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cs.CV2022

Progressively Dual Prior Guided Few-shot Semantic Segmentation

Qinglong Cao, Yuntian Chen, Xiwen Yao +1

Few-shot semantic segmentation task aims at performing segmentation in query images with a few annotated support samples. Currently, few-shot segmentation methods mainly focus on l…

cs.CV202237 cited

Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

Yuanwei Liu, Nian Liu, Xiwen Yao +1

Few-shot semantic segmentation aims to segment the target objects in query under the condition of a few annotated support images. Most previous works strive to mine more effective…

cs.CV20225 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.CV20226 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…