PASCAL VOC 2012

Pascal VOC 2012 is a dataset used for evaluating semantic segmentation algorithms, containing annotated images for object detection and classification tasks.

Papers using PASCAL VOC 2012 (16)

Golden Cudgel Network for Real-Time Semantic Segmentation2025 · 18 citesContrastive Prompt Clustering for Weakly Supervised Semantic Segmentation2025Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic Segmentation2025Semi-supervised Semantic Segmentation with Multi-Constraint Consistency Learning2025Pyramid Scene Parsing Network2016 · 15,595 citesLocalizing Objects with Self-Supervised Transformers and no Labels2021 · 107 citesCausal Intervention for Weakly-Supervised Semantic Segmentation2020 · 70 citesComprehensive Attention Self-Distillation for Weakly-Supervised Object Detection2020 · 66 citesObject-Aware Instance Labeling for Weakly Supervised Object Detection2019 · 61 citesCRCNet: Few-shot Segmentation with Cross-Reference and Region-Global Conditional Networks2022 · 27 citesBoundary-aware Instance Segmentation2016 · 9 citesPseudo Mask Augmented Object Detection2018 · 5 citesObject Discovery via Contrastive Learning for Weakly Supervised Object Detection2022 · 2 citesHuman Action Recognition in Still Images Using ConViT2023 · 1 citesDual Progressive Transformations for Weakly Supervised Semantic Segmentation2022COMNet: Co-Occurrent Matching for Weakly Supervised Semantic Segmentation2023