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20172026
most citedPer-Pixel Classification is Not All You Need for Semantic Segmentation

167 citations · 774 across the 23 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.CV2021★ 64 cited

Mask2Former for Video Instance Segmentation

Bowen Cheng, Anwesa Choudhuri, Ishan Misra +3

We find Mask2Former also achieves state-of-the-art performance on video instance segmentation without modifying the architecture, the loss or even the training pipeline. In this re…

cs.CV2021★ 133 cited

Masked-attention Mask Transformer for Universal Image Segmentation

Bowen Cheng, Ishan Misra, Alexander G. Schwing +2

Image segmentation is about grouping pixels with different semantics, e.g., category or instance membership, where each choice of semantics defines a task. While only the semantics…

cs.CV2021★ 167 cited

Per-Pixel Classification is Not All You Need for Semantic Segmentation

Bowen Cheng, Alexander G. Schwing, Alexander Kirillov

Modern approaches typically formulate semantic segmentation as a per-pixel classification task, while instance-level segmentation is handled with an alternative mask classification…

cs.CV2021★ 5 cited

Pseudo-IoU: Improving Label Assignment in Anchor-Free Object Detection

Jiachen Li, Bowen Cheng, Rogerio Feris +4

Current anchor-free object detectors are quite simple and effective yet lack accurate label assignment methods, which limits their potential in competing with classic anchor-based…

cs.CV2021★ 4 cited

Pointly-Supervised Instance Segmentation

Bowen Cheng, Omkar Parkhi, Alexander Kirillov

We propose an embarrassingly simple point annotation scheme to collect weak supervision for instance segmentation. In addition to bounding boxes, we collect binary labels for a set…

cs.CV2021★ 28 cited

Boundary IoU: Improving Object-Centric Image Segmentation Evaluation

Bowen Cheng, Ross Girshick, Piotr Dollár +2

We present Boundary IoU (Intersection-over-Union), a new segmentation evaluation measure focused on boundary quality. We perform an extensive analysis across different error types…