https://github.com/ywyeli/place3d
공식 코드Is Your LiDAR Placement Optimized for 3D Scene Understanding?
Papers with Code 아카이브
Scene Understanding
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 3
- 보존된 평가 기록
- 5
Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yz93/anchor-diff-VOS
공식 코드https://github.com/z-x-yang/AOT
공식 코드Associating Objects with Transformers for Video Object Segmentation
https://github.com/z-x-yang/CFBI
공식 코드Collaborative Video Object Segmentation by Foreground-Background Integration
https://github.com/zamling/psalm
공식 코드https://github.com/zaplm/dc-sam
공식 코드DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
https://github.com/zboyd2/SBM-surface-tension
공식 코드https://github.com/zc-zhao/drivemonkey
공식 코드Extending Large Vision-Language Model for Diverse Interactive Tasks in Autonomous Driving
https://github.com/zehuichen123/bevdistill
공식 코드BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detection
https://github.com/zestfuljx/cob-gs
공식 코드COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian Splitting
https://github.com/zgojcic/Rigid3DSceneFlow
공식 코드https://github.com/zhang-tao-whu/DVIS_Plus
공식 코드DVIS++: Improved Decoupled Framework for Universal Video Segmentation
https://github.com/zhang-vislab/iros2024-lossdistillationweightedcd
공식 코드Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance
https://github.com/zhanglab-deepneurocoglab/csegg
공식 코드Adaptive Visual Scene Understanding: Incremental Scene Graph Generation
https://github.com/zhaochongan/the-mask
공식 코드Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation
https://github.com/zhaoyucs/vsd
공식 코드Generating Visual Spatial Description via Holistic 3D Scene Understanding
https://github.com/zhe-sapi/udass
공식 코드https://github.com/zhen6618/eprecon
공식 코드EPRecon: An Efficient Framework for Real-Time Panoptic 3D Reconstruction from Monocular Video
https://github.com/zhihou7/HOI-CL
공식 코드Detecting Human-Object Interaction via Fabricated Compositional Learning
https://github.com/zhihou7/HOI-CL-OneStage
공식 코드Affordance Transfer Learning for Human-Object Interaction Detection
https://github.com/zhimin-c/bridge3d
공식 코드Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
https://github.com/zhiweihhh/cvpr2022-rvos-challenge
공식 코드1st Place Solution for YouTubeVOS Challenge 2022: Referring Video Object Segmentation
https://github.com/zhonghuayi/focusflow_official
공식 코드FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving
https://github.com/zhouhaocv/RLM-Net
공식 코드https://github.com/zhoustan/camsam2
공식 코드https://github.com/zht8506/qmvos
공식 코드https://github.com/zhugekongkong/sgg-g2s
공식 코드From General to Specific: Informative Scene Graph Generation via Balance Adjustment
https://github.com/zhyever/monocular-depth-estimation-toolbox
공식 코드BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation
https://github.com/zifuwan/sigma
공식 코드Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation
https://github.com/zihangm/Differentiable-LP-Layer
공식 코드Physarum Powered Differentiable Linear Programming Layers and Applications
https://github.com/zihangm/Physarum-Differentiable-LP-Layer
공식 코드Physarum Powered Differentiable Linear Programming Layers and Applications
https://github.com/zikai1/oareg
공식 코드Occlusion-aware Non-Rigid Point Cloud Registration via Unsupervised Neural Deformation Correntropy
https://github.com/ziplab/mpvss
공식 코드https://github.com/zitongzhan/mmtracking/tree/zitongzhan/rovis/configs/vis/rovis
공식 코드Robust Online Video Instance Segmentation with Track Queries
https://github.com/zju-jiangqi/ciada
공식 코드Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond Aberrations
https://github.com/zlai0/CorrFlow
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.