Alternatives and similar repositories for UnsupObjSeg:

Users that are interested in UnsupObjSeg are comparing it to the libraries listed below

• jd730 / EOPSN
  [CVPR 2021] Exemplar-Based Open-Set Panoptic Segmentation Network (EOPSN)
  ☆51Updated 2 years ago
• MehmetAygun / demistfy_correspondence
  Code for the ECCV22 paper Demystifying Unsupervised Semantic Correspondence Estimation
  ☆13Updated 2 years ago
• CurryYuan / X-Trans2Cap
  [CVPR 2022] X-Trans2Cap: Cross-Modal Knowledge Transfer using Transformer for 3D Dense Captioning
  ☆34Updated 2 years ago
• zpbao / Discovery_Obj_Move
  ☆43Updated last year
• jasonbian97 / flowwalk
  ☆32Updated 2 years ago
• juhongm999 / dhpf
  Official PyTorch Implementation of Dynamic Hyperpixel Flow, ECCV 2020
  ☆39Updated 2 years ago
• huyvvo / LOD
  [NeurIPS 2021] Official Matlab implementation of LOD: Large-Scale Unsupervised Object Discovery.
  ☆21Updated 2 years ago
• rehg-lab / lowshot-shapebias
  Learning low-shot object classification with explicit shape bias learned from point clouds
  ☆50Updated 3 years ago
• VITA-Group / Simple3D-Former
  [Preprint 2022] “Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer?” by Yi Wang, Zhiwen Fan, Tianlong Chen, Hehe Fan, Zh…
  ☆61Updated 2 years ago
• klnavaneet / ssl_3d_recon
  Code release for "From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks" (CVPR 2020)
  ☆22Updated 4 years ago
• facebookresearch / PLRC
  Code for Point-Level Regin Contrast (https//arxiv.org/abs/2202.04639)
  ☆35Updated 2 years ago
• ZiweiWangTHU / ISL
  This is the official pytorch implementation for the paper: Instance Similarity Learning for Unsupervised Feature Representation.
  ☆21Updated 3 years ago
• vobecant / DriveAndSegment
  ☆55Updated 4 months ago
• shamitlal / CoCoNets
  ☆26Updated 2 years ago
• liuzhengzhe / 3D-to-2D-Distillation-for-Indoor-Scene-Parsing
  CVPR 2021 Oral https://arxiv.org/abs/2104.02243
  ☆47Updated last year
• SAITPublic / SlotVPS
  The official project for the paper: Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation, CVPR 2022
  ☆14Updated 2 years ago
• YangtaoWANG95 / TokenCut_video
  Pytorch implementation of "TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut"
  ☆59Updated 2 years ago
• tgxs002 / wikiscenes
  Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision. ICCV 2021.
  ☆43Updated 10 months ago
• wookiekim / transformatcher
  Official PyTorch implementation of TransforMatcher: Match-to-Match Attention for Semantic Correspondence (CVPR 2022 Poster)
  ☆38Updated 2 years ago
• elicassion / 3DTRL
  Code for NeurIPS 2022 paper "Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space"
  ☆20Updated last year
• MSiam / video_class_agnostic_segmentation
  Official Datasets and Implementation from our Paper "Video Class Agnostic Segmentation in Autonomous Driving".
  ☆30Updated 6 months ago
• yanx27 / CLEVR3D
  CLEVR3D Dataset: Comprehensive Visual Question Answering on Point Clouds through Compositional Scene Manipulation
  ☆17Updated last year
• 16lemoing / ccvs
  CCVS: Context-aware Controllable Video Synthesis
  ☆22Updated 3 years ago
• KaiChen1998 / MultiSiam
  Official PyTorch implementation of MultiSiam in ICCV 2021 (https://arxiv.org/abs/2108.12178)
  ☆22Updated 3 years ago
• TerenceCYJ / 4DContrast
  4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding, ECCV 2022
  ☆17Updated 2 years ago
• XiSHEN0220 / SSR
  (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"
  ☆31Updated 3 years ago
• karazijal / probable-motion
  Unsupervised Multi-object Segmentation by Predicting Probable Motion Patterns
  ☆16Updated 2 years ago
• ShuaiyiHuang / SCorrSAN
  Official Code for ECCV2022: Learning Semantic Correspondence with Sparse Annotations
  ☆18Updated 2 years ago
• chrischoy / SpatioTemporalSegmentation-ScanNet
  ☆23Updated 4 years ago
• mihirp1998 / Slot-TTA
  Slot-TTA shows that test-time adaptation using slot-centric models can improve image segmentation on out-of-distribution examples.
  ☆26Updated last year