Papers Multi-object discovery
“Multi-object discovery” 태그가 달린 논문 9편 · 필터 해제
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+1PatchNet: Unsupervised Object Discovery based on Patch Embedding
We demonstrate that frequently appearing objects can be discovered by training randomly sampled patches from a small number of images (100 to 200) by self-supervision. Key to this approach is the pattern space, a latent …
ClusteringMulti-object discoveryObjectObject DiscoveryLarge-Scale Unsupervised Object Discovery
Existing approaches to unsupervised object discovery (UOD) do not scale up to large datasets without approximations that compromise their performance. We propose a novel formulation of UOD as a ranking problem, amenable …
Multi-object discoveryObjectObject DiscoverySingle-object discoveryToward unsupervised, multi-object discovery in large-scale image collections
This paper addresses the problem of discovering the objects present in a collection of images without any supervision. We build on the optimization approach of Vo et al. (CVPR'19) with several key novelties: (1) We propo…
Multi-object colocalizationMulti-object discoveryObject DiscoveryRegion Proposal+2