Multi-object discovery
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Benchmarks
Most implemented
DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
Large-Scale Unsupervised Object Discovery
Toward unsupervised, multi-object discovery in large-scale image collections
Papers
Motion-Refined DINOSAUR for Unsupervised Multi-Object Discovery
Unsupervised multi-object discovery (MOD) aims to detect and localize distinct object instances in visual scenes without any form of human supervision. Recent approaches leverage object-centric learning (OCL) and motion …
Multi-object discoveryMotion SegmentationxMOD: Cross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D motion
Object discovery, which refers to the task of localizing objects without human annotations, has gained significant attention in 2D image analysis. However, despite this growing interest, it remains under-explored in 3D d…
Multi-object discoveryObjectObject DiscoveryObject LocalizationCross-Modal Distillation for 2D/3D Multi-Object Discovery from 2D Motion
Object discovery, which refers to the task of localizing objects without human annotations, has gained significant attention in 2D image analysis. However, despite this growing interest, it remains under-explored in …
Multi-object discoveryObjectObject DiscoveryObject LocalizationDiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection
Class-agnostic object detection (OD) can be a cornerstone or a bottleneck for many downstream vision tasks. Despite considerable advancements in bottom-up and multi-object discovery methods that leverage basic visual cue…
Class-agnostic Object DetectionMulti-object discoveryObjectobject-detection+3Multi-Object Discovery by Low-Dimensional Object Motion
Recent work in unsupervised multi-object segmentation shows impressive results by predicting motion from a single image despite the inherent ambiguity in predicting motion without the next image. On the other hand, the s…
Depth EstimationMonocular Depth EstimationMulti-object discoveryObject+3Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots
We introduce a method to segment the visual field into independently moving regions, trained with no ground truth or supervision. It consists of an adversarial conditional encoder-decoder architecture based on Slot Atten…
DecoderMotion SegmentationMulti-object discoveryObject Discovery+1