Pascal VOC

Pascal VOC is a dataset that contains annotated images for object detection and segmentation, used to evaluate the performance of object recognition algorithms.

Papers using Pascal VOC (9)

BareBones: Benchmarking Zero-Shot Geometric Comprehension in VLMs2026A novel Framework for Open-Vocabulary Multi-Object Recognition using CLIP2026DEX-AR: A Dynamic Explainability Method for Autoregressive Vision-Language Models2026A Training-Free Guess What Vision Language Model from Snippets to Open-Vocabulary Object Detection2026SJTU:Spatial judgments in multimodal models towards unified segmentation through coordinate detection2024VLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection via Vision-Language Model2024 · 13 citesRethinking Sparse Lexical Representations for Image Retrieval in the Age of Rising Multi-Modal Large Language Models2024 · 1 citesEmergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models2023Text-Region Matching for Multi-Label Image Recognition with Missing Labels2024