PASCAL-Context
Emerging6papers using it
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2016first seen
The 'Pascal Context' dataset is a benchmark that contains annotated images for evaluating multi-task dense prediction tasks in computer vision.
Papers using PASCAL-Context (6)
- Sparse Attention for Dense Open-Vocabulary Prediction in CLIPLeMoRe: Learn More Details for Lightweight Semantic SegmentationDecoder Denoising Pretraining for Semantic SegmentationFeature Selective Transformer for Semantic Image SegmentationRegion-based semantic segmentation with end-to-end trainingTransformer Scale Gate for Semantic Segmentation