https://github.com/PKUbahuangliuhe/CBNet
공식 코드CBNet: A Novel Composite Backbone Network Architecture for Object Detection
Papers with Code 아카이브
Instance Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 17
- 평가표
- 36
- 보존된 평가 기록
- 338
Instance Segmentation is a computer vision task that involves identifying and separating individual objects within an image, including detecting the boundaries of each object and assigning a unique label to each object. The goal of instance segmentation is to produce a pixel-wise segmentation map of the image, where each pixel is assigned to a specific object instance.
Image Credit: Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers, CVPR'21
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/PaddlePaddle/PaddleClas
공식 코드HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network
https://github.com/Pointcept/OpenIns3D
공식 코드OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation
https://github.com/ProvenceStar/PartGLEE
공식 코드PartGLEE: A Foundation Model for Recognizing and Parsing Any Objects
https://github.com/RPL-CS-UCL/UCL-AffCorrs
공식 코드https://github.com/RayYoh/SGIFormer
공식 코드https://github.com/RobertLuo1/HDC
공식 코드https://github.com/RobertLuo1/NeurIPS2023_SOC
공식 코드SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation
https://github.com/SHI-Labs/CompFeat-for-Video-Instance-Segmentation
공식 코드CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation
https://github.com/SHI-Labs/Convolutional-MLPs
공식 코드https://github.com/SHI-Labs/Mask-Selection-Networks
공식 코드MSN: Efficient Online Mask Selection Network for Video Instance Segmentation
https://github.com/SHI-Labs/Neighborhood-Attention-Transformer
공식 코드https://github.com/SHI-Labs/OneFormer
공식 코드OneFormer: One Transformer to Rule Universal Image Segmentation
https://github.com/SIAAAAAA/MMT-PSM
공식 코드Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation
https://github.com/SLDGroup/GreedyViG
공식 코드GreedyViG: Dynamic Axial Graph Construction for Efficient Vision GNNs
https://github.com/SMKamrulHasan/UNetPlus
공식 코드https://github.com/Scalsol/RepPointsV2
공식 코드RepPoints V2: Verification Meets Regression for Object Detection
https://github.com/Sekunde/3D-SIS
공식 코드https://github.com/SeokjuLee/Insta-DM
공식 코드Instance-wise Depth and Motion Learning from Monocular Videos
https://github.com/Seung-Hun-Lee/CAVIS
공식 코드https://github.com/ShangHua-Gao/RFNext
공식 코드RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks
https://github.com/Sharath-girish/LTH-ObjectRecognition
공식 코드https://github.com/ShoufaChen/CycleMLP
공식 코드https://github.com/ShuLiu1993/PANet
공식 코드https://github.com/Smartory/Augmentory
공식 코드AugmenTory: A Fast and Flexible Polygon Augmentation Library
https://github.com/SonginCV/MAF_HDA
공식 코드Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion
https://github.com/StevenGrove/LearnableTreeFilterV2
공식 코드Rethinking Learnable Tree Filter for Generic Feature Transform
https://github.com/SwinTransformer/Feature-Distillation
공식 코드Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation
https://github.com/SysCV/bdd100k-models
공식 코드BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning
https://github.com/SysCV/transfiner
공식 코드https://github.com/Tete-Xiao/ReSim
공식 코드https://github.com/TonyLianLong/CrossMAE
공식 코드https://github.com/TonyLianLong/RCF-UnsupVideoSeg
공식 코드Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
https://github.com/Uehwan/SimVODIS
공식 코드SimVODIS: Simultaneous Visual Odometry, Object Detection, and Instance Segmentation
https://github.com/VCCIV/BLVD
공식 코드BLVD: Building A Large-scale 5D Semantics Benchmark for Autonomous Driving
https://github.com/VDIGPKU/CBNetV2
공식 코드CBNet: A Composite Backbone Network Architecture for Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.