https://github.com/vincentvanderbrugge/pickandscan
공식 코드PickScan: Object discovery and reconstruction from handheld interactions
Papers with Code 아카이브
Object Discovery
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Object Discovery is the task of identifying previously unseen objects.
Source: Unsupervised Object Discovery and Segmentation of RGBD-images
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vision-sjtu/usot
공식 코드https://github.com/vision4robotics/udat
공식 코드Unsupervised Domain Adaptation for Nighttime Aerial Tracking
https://github.com/vlsf/hkmemory
공식 코드https://github.com/yangcaoai/CoDA_NeurIPS2023
공식 코드https://github.com/zadaianchuk/comus
공식 코드Unsupervised Semantic Segmentation with Self-supervised Object-centric Representations
https://github.com/zpbao/discovery_obj_move
공식 코드https://github.com/zpbao/motok
공식 코드https://github.com/Gaurav14cs17/YOLOE
Learning Open-World Object Proposals without Learning to Classify
https://github.com/GuessWhatGame/guesswhat
GuessWhat?! Visual object discovery through multi-modal dialogue
https://github.com/HHousen/object-discovery-pytorch
https://github.com/JohannesTheo/multi_object_datasets_torch
https://github.com/KostadinovShalon/oln-mask
Learning Open-World Object Proposals without Learning to Classify
https://github.com/Michedev/MONet-pytorch
https://github.com/Michedev/slot-attention-pytorch
https://github.com/SaoYan/LearnToPayAttention
https://github.com/XiSHEN0220/SegSwap
Learning Co-segmentation by Segment Swapping for Retrieval and Discovery
https://github.com/YangtaoWANG95/TokenCut
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
https://github.com/a-imamshah/savi-pytorch
https://github.com/a-imamshah/slotattention.jl
https://github.com/adityabingi/Slot-Attention
https://github.com/aljosaosep/kitti-track-collection
Large-Scale Object Discovery and Detector Adaptation from Unlabeled Video
https://github.com/anandhupvr/Mining-Objects
Object Discovery From a Single Unlabeled Image by Mining Frequent Itemset With Multi-scale Features
https://github.com/azizanlab/unlimitd
https://github.com/basilevh/object-discovery-cp-gan
https://github.com/baudm/MONet-pytorch
https://github.com/borisdayma/clip-jax
https://github.com/caoquanjie/LearnToPayAttention
https://github.com/chwilms/sos
Learning Open-World Object Proposals without Learning to Classify
https://github.com/crowdflowTUe/stampnet
https://github.com/deepmind/multi_object_datasets
https://github.com/google-deepmind/spriteworld
https://github.com/gorkaydemir/DINOSAUR
Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames
https://github.com/havrylovv/isegprobe
LiFT: A Surprisingly Simple Lightweight Feature Transform for Dense ViT Descriptors
https://github.com/ibaiGorordo/ONNX-Object-Localization-Network
Learning Open-World Object Proposals without Learning to Classify
https://github.com/ibrahimSouleiman/GuessWhat
GuessWhat?! Visual object discovery through multi-modal dialogue
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.