https://github.com/mit-han-lab/bevfusion
공식 코드BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
Papers with Code 아카이브
Scene Segmentation
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Scene segmentation is the task of splitting a scene into its various object components.
Image adapted from Temporally coherent 4D reconstruction of complex dynamic scenes.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mit-han-lab/pvcnn
공식 코드https://github.com/mlvlab/spotr
공식 코드Self-positioning Point-based Transformer for Point Cloud Understanding
https://github.com/mobarakol/Surgical_SceneGraph_Generation
공식 코드Learning and Reasoning with the Graph Structure Representation in Robotic Surgery
https://github.com/mobarakol/p-cd
공식 코드Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation
https://github.com/msraig/pfcnn
공식 코드PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames
https://github.com/nnizhang/SMAC
공식 코드https://github.com/patrick-tssn/VSTAR
공식 코드https://github.com/physiologicailab/sam-cl
공식 코드Self-adversarial Multi-scale Contrastive Learning for Semantic Segmentation of Thermal Facial Images
https://github.com/pmeletis/hierarchical-semantic-segmentation
공식 코드On Boosting Semantic Street Scene Segmentation with Weak Supervision
https://github.com/potsui99/unirgb-ir
공식 코드UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter Tuning
https://github.com/prachigarg23/mdil-ss
공식 코드https://github.com/princeton-computational-imaging/DirtyPixels
공식 코드Dirty Pixels: Towards End-to-End Image Processing and Perception
https://github.com/qujx/ddnet
공식 코드https://github.com/robot-learning-freiburg/BEVCar
공식 코드BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation
https://github.com/rstrudel/segmenter
공식 코드https://github.com/ruipingl/miss
공식 코드Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation
https://github.com/runsong123/unified-lift
공식 코드Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting
https://github.com/salmank255/ROAD_Waymo_Baseline
공식 코드ROAD-Waymo: Action Awareness at Scale for Autonomous Driving
https://github.com/shachoi/HANet
공식 코드https://github.com/shachoi/RobustNet
공식 코드https://github.com/shaohuadong2021/dplnet
공식 코드Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning
https://github.com/shaohuadong2021/egfnet
공식 코드Edge-aware Guidance Fusion Network for RGB Thermal Scene Parsing
https://github.com/shenglandu/pushboundary
공식 코드Push-the-Boundary: Boundary-aware Feature Propagation for Semantic Segmentation of 3D Point Clouds
https://github.com/shjung13/standardized-max-logits
공식 코드https://github.com/shyam671/mask2anomaly-unmasking-anomalies-in-road-scene-segmentation
공식 코드https://github.com/sohyun-l/fifo
공식 코드FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation
https://github.com/speedinghzl/CCNet
공식 코드https://github.com/taozh2017/RGBD-SODsurvey
공식 코드https://github.com/taozh2017/spnet
공식 코드https://github.com/tencentyouturesearch/highlightdetection-clc
공식 코드https://github.com/tensorflow/models
공식 코드Naive-Student: Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation
https://github.com/theeighthday/co-teaching
공식 코드Co-Teaching for Unsupervised Domain Adaptation and Expansion
https://github.com/uark-cviu/bimal
공식 코드BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
https://github.com/uark-cviu/fredom
공식 코드FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding
https://github.com/uva-dsa/auto_surgical_context2gesture
공식 코드Towards Surgical Context Inference and Translation to Gestures
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.