Pascal VOC
Canonical31papers using it
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2016first seen
An object-detection and segmentation benchmark of 20 object categories from the PASCAL Visual Object Classes challenge.
Papers using Pascal VOC (31)
- PixCon: Clean-Positive Contrastive Learning for Foundation-Model Semi-Supervised SegmentationHSA: Hierarchical Slot Attention for Multi-granularity Scene-DecompositionLipSSD: Lipschitz-Constrained Single-Shot Detection for Adversarially Robust Object DetectionSparse Attention for Dense Open-Vocabulary Prediction in CLIPPractical Insights into Semi-Supervised Object Detection ApproachesExploring Open-Vocabulary Object Recognition in Images using CLIPSSR: Semantic and Spatial Rectification for CLIP-based Weakly Supervised SegmentationSelective Masking based Self-Supervised Learning for Image Semantic SegmentationA Training-Free Framework for Open-Vocabulary Image Segmentation and Recognition with EfficientNet and CLIPLeveraging Out-of-Distribution Unlabeled Images: Semi-Supervised Semantic Segmentation with an Open-Vocabulary ModelVisual Textualization for Image Prompted Object DetectionDecoupling Classifier for Boosting Few-shot Object Detection and Instance SegmentationApproximate Size Targets Are Sufficient for Accurate Semantic
Segmentationk-fold Subsampling based Sequential Backward Feature Elimination'part'ly First Among Equals: Semantic Part-based Benchmarking For State-of-the-art Object Recognition SystemsFew-Shot Object Detection with Fully Cross-TransformerWeakly- and Semi-Supervised Panoptic SegmentationDomain Adaptation for Object Detection via Style ConsistencyFeature-Driven Super-Resolution for Object DetectionMulti-class Token Transformer for Weakly Supervised Semantic
SegmentationDeep Object Co-SegmentationSemi-convolutional Operators for Instance SegmentationTowards Few-Annotation Learning for Object Detection: Are
Transformer-based Models More Efficient ?Spatial Reasoning for Few-Shot Object DetectionYOLO-Former: YOLO Shakes Hand With ViTDETReg: Unsupervised Pretraining with Region Priors for Object DetectionTime-rEversed diffusioN tEnsor Transformer: A new TENET of Few-Shot
Object DetectionIvaNet: Learning to jointly detect and segment objets with the help of
Local Top-Down ModulesSeqCo-DETR: Sequence Consistency Training for Self-Supervised Object
Detection with TransformersDenseDINO: Boosting Dense Self-Supervised Learning with Token-Based
Point-Level ConsistencyCLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic
Segmentation For-Free