Unsupervised Object Localization
3개 벤치마크 · 논문 12편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
PEEKABOO: Hiding parts of an image for unsupervised object localization
CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free
Unsupervised Object Localization with Representer Point Selection
Optical Flow boosts Unsupervised Localization and Segmentation
Papers
Enhancing Object Discovery for Unsupervised Instance Segmentation and Object Detection
We propose Cut-Once-and-LEaRn (COLER), a simple approach for unsupervised instance segmentation and object detection. COLER first uses our developed CutOnce to generate coarse pseudo labels, then enables the detector to …
Unsupervised Instance SegmentationUnsupervised Object LocalizationObject SegmentationObject DetectionPEEKABOO: Hiding parts of an image for unsupervised object localization
Localizing objects in an unsupervised manner poses significant challenges due to the absence of key visual information such as the appearance, type and number of objects, as well as the lack of labeled object classes typ…
Objectobject-detectionObject DetectionObject Discovery+4Unsupervised Object Localization in the Era of Self-Supervised ViTs: A Survey
The recent enthusiasm for open-world vision systems show the high interest of the community to perform perception tasks outside of the closed-vocabulary benchmark setups which have been so popular until now. Being able t…
ObjectObject LocalizationUnsupervised Object LocalizationCLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free
The emergence of CLIP has opened the way for open-world image perception. The zero-shot classification capabilities of the model are impressive but are harder to use for dense tasks such as image segmentation. Several me…
Image SegmentationObject LocalizationOpen Vocabulary Semantic SegmentationOpen-Vocabulary Semantic Segmentation+6Unsupervised Object Localization with Representer Point Selection
We propose a novel unsupervised object localization method that allows us to explain the predictions of the model by utilizing self-supervised pre-trained models without additional finetuning. Existing unsupervised and s…
ObjectObject LocalizationUnsupervised Object LocalizationOptical Flow boosts Unsupervised Localization and Segmentation
Unsupervised localization and segmentation are long-standing robot vision challenges that describe the critical ability for an autonomous robot to learn to decompose images into individual objects without labeled data. T…
Lifelong learningObjectObject LocalizationOptical Flow Estimation+4