https://github.com/lab206/adaptiveclick
공식 코드AdaptiveClick: Clicks-aware Transformer with Adaptive Focal Loss for Interactive Image Segmentation
Papers with Code 아카이브
2D Semantic Segmentation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/laihuiyuan/Pre-trained-formality-transfer
공식 코드Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer
https://github.com/laihuiyuan/eval-formality-transfer
공식 코드Human Judgement as a Compass to Navigate Automatic Metrics for Formality Transfer
https://github.com/laihuiyuan/multilingual-tst
공식 코드Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer
https://github.com/lalithjets/domain-adaptation-in-mtl
공식 코드https://github.com/lalithjets/global-reasoned-multi-task-model
공식 코드Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding
https://github.com/lambert-x/catenorm
공식 코드CateNorm: Categorical Normalization for Robust Medical Image Segmentation
https://github.com/lancasterli/refsam
공식 코드RefSAM: Efficiently Adapting Segmenting Anything Model for Referring Video Object Segmentation
https://github.com/lancercat/moose
공식 코드MOoSE: Multi-Orientation Sharing Experts for Open-set Scene Text Recognition
https://github.com/lancopku/Augmented_Data_for_FST
공식 코드https://github.com/lancopku/unpaired-sentiment-translation
공식 코드Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach
https://github.com/lanlan96/3drm
공식 코드https://github.com/lanmng/sitvos
공식 코드Siamese Network with Interactive Transformer for Video Object Segmentation
https://github.com/lanqingl/scs
공식 코드Visual Prompt Selection for In-Context Learning Segmentation
https://github.com/lans1ng/pointsam
공식 코드PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images
https://github.com/large-ocr-model/large-ocr-model.github.io
공식 코드https://github.com/lars76/segmentation_activations
공식 코드https://github.com/lartpang/ovcamo
공식 코드https://github.com/lartpang/zoomnet
공식 코드Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection
https://github.com/lastbasket/surgtpgs
공식 코드SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting
https://github.com/laura-wang/video_repres_sts
공식 코드Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics
https://github.com/ldenninger/camcontexti2v
공식 코드https://github.com/ldkong1205/LaserMix
공식 코드Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous Driving
https://github.com/ldkong1205/calib3d
공식 코드Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding
https://github.com/ldkong1205/openess
공식 코드OpenESS: Event-based Semantic Scene Understanding with Open Vocabularies
https://github.com/leaplabthu/deep-incubation
공식 코드Deep Incubation: Training Large Models by Divide-and-Conquering
https://github.com/leaplabthu/model-assembling
공식 코드Deep Incubation: Training Large Models by Divide-and-Conquering
https://github.com/leejieyu13/lidarcameradataset
공식 코드2D LiDAR and Camera Fusion Using Motion Cues for Indoor Layout Estimation
https://github.com/leesoon1984/cmmt-net
공식 코드Cross-head mutual Mean-Teaching for semi-supervised medical image segmentation
https://github.com/lei-wang-github/DeepPS2
공식 코드DeepPS2: Revisiting Photometric Stereo Using Two Differently Illuminated Images
https://github.com/leiluk1/gaze-based-segmentation
공식 코드https://github.com/leipingjie/sam2video
공식 코드https://github.com/leipingjie/samshadow
공식 코드https://github.com/leiyaocui/strap
공식 코드STRAP: Structured Object Affordance Segmentation with Point Supervision
https://github.com/lelimite4444/BridgeDepthFlow
공식 코드Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence
https://github.com/lemmersj/ground-truth-or-daer
공식 코드Ground-truth or DAER: Selective Re-query of Secondary Information
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.