https://github.com/opengvlab/dcnv4
공식 코드Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications
Papers with Code 아카이브
Semantic Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/opengvlab/hulk
공식 코드Hulk: A Universal Knowledge Translator for Human-Centric Tasks
https://github.com/opengvlab/humanbench
공식 코드Hulk: A Universal Knowledge Translator for Human-Centric Tasks
https://github.com/opengvlab/instruct2act
공식 코드Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
https://github.com/opengvlab/internimage
공식 코드InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
https://github.com/opengvlab/mutr
공식 코드Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation
https://github.com/opengvlab/piip
공식 코드https://github.com/opengvlab/unihcp
공식 코드https://github.com/openmedlab/medlsam
공식 코드MedLSAM: Localize and Segment Anything Model for 3D CT Images
https://github.com/openmedlab/mis-fm
공식 코드https://github.com/opennlplab/acr_wsss
공식 코드All-pairs Consistency Learning for Weakly Supervised Semantic Segmentation
https://github.com/opennlplab/avs-bidirectional
공식 코드Improving Audio-Visual Segmentation with Bidirectional Generation
https://github.com/opennlplab/avsbench
공식 코드https://github.com/openrobotlab/ov_parts
공식 코드https://github.com/openseg-group/mlseg
공식 코드RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation
https://github.com/openseg-group/openseg.pytorch
공식 코드https://github.com/openseg-group/rankseg
공식 코드RankSeg: Adaptive Pixel Classification with Image Category Ranking for Segmentation
https://github.com/opradelle/2dguidedlight3d
공식 코드Lightweight integration of 3D features to improve 2D image segmentation
https://github.com/orange-czh/mamba-sea
공식 코드https://github.com/oranshayer/BRRF
공식 코드Enhancing Generic Segmentation with Learned Region Representations
https://github.com/oravus/lostX
공식 코드LoST? Appearance-Invariant Place Recognition for Opposite Viewpoints using Visual Semantics
https://github.com/orhir/3d-shape-consistent-gan
공식 코드Shape-consistent Generative Adversarial Networks for multi-modal Medical segmentation maps
https://github.com/orhir/shape-consistent-generative-adversarial-networks-for-multi-modal-medical-segmentation-maps
공식 코드Shape-consistent Generative Adversarial Networks for multi-modal Medical segmentation maps
https://github.com/orion-ai-lab/hephaestus
공식 코드Hephaestus: A large scale multitask dataset towards InSAR understanding
https://github.com/orion-ai-lab/s4a
공식 코드https://github.com/orsic/swiftnet
공식 코드https://github.com/ortonwang/pcdal
공식 코드https://github.com/ortonwang/plgdf
공식 코드https://github.com/ortonwang/scribblevs
공식 코드https://github.com/oshadajay/CeyMo
공식 코드CeyMo: See More on Roads -- A Novel Benchmark Dataset for Road Marking Detection
https://github.com/oskarnatan/deepipc
공식 코드DeepIPC: Deeply Integrated Perception and Control for an Autonomous Vehicle in Real Environments
https://github.com/oskarnatan/end-to-end-driving
공식 코드End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent
https://github.com/ostadabbas/prior-aware-synthetic-data-generation-pasyn-
공식 코드Prior-Aware Synthetic Data to the Rescue: Animal Pose Estimation with Very Limited Real Data
https://github.com/osupcvlab/mobileunetr
공식 코드https://github.com/osupcvlab/segformer3d
공식 코드SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation
https://github.com/osvai/af-dcd
공식 코드Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.