https://github.com/pinxueguo/x-prompt
공식 코드X-Prompt: Multi-modal Visual Prompt for Video Object Segmentation
Papers with Code 아카이브
Scene Parsing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 9
- 평가표
- 2
- 보존된 평가 기록
- 3
Scene parsing is to segment and parse an image into different image regions associated with semantic categories, such as sky, road, person, and bed. MIT Description
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/pipixin321/holmesvau
공식 코드Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity
https://github.com/pjlab-adg/gpt4v-ad-exploration
공식 코드On the Road with GPT-4V(ision): Early Explorations of Visual-Language Model on Autonomous Driving
https://github.com/pjlallen/s2former-or
공식 코드S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in OR
https://github.com/pkyong95/PCVOS
공식 코드https://github.com/plusmultiply/mprm
공식 코드Multi-Path Region Mining For Weakly Supervised 3D Semantic Segmentation on Point Clouds
https://github.com/ponimatkin/ssl-vos
공식 코드A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
https://github.com/pqhieu/JSIS3D
공식 코드https://github.com/praneeth11009/LIGHTEN-Learning-Interactions-with-Graphs-and-Hierarchical-TEmporal-Networks-for-HOI
공식 코드LIGHTEN: Learning Interactions with Graph and Hierarchical TEmporal Networks for HOI in videos
https://github.com/pratulsrinivasan/lighthouse
공식 코드Lighthouse: Predicting Lighting Volumes for Spatially-Coherent Illumination
https://github.com/prbonn/3diss
공식 코드Towards Generating Realistic 3D Semantic Training Data for Autonomous Driving
https://github.com/prbonn/simp
공식 코드Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor Localization
https://github.com/prgumd/0-MMS
공식 코드0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera
https://github.com/prgumd/SalientDSO
공식 코드https://github.com/prijatelj/bayesian_eval_ground_truth-free
공식 코드A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition Tasks
https://github.com/princeton-computational-imaging/DirtyPixels
공식 코드Dirty Pixels: Towards End-to-End Image Processing and Perception
https://github.com/princetonvisualai/imagenet-face-obfuscation
공식 코드https://github.com/prismformore/InvPT
공식 코드InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene Understanding
https://github.com/prismformore/multi-task-transformer
공식 코드InvPT++: Inverted Pyramid Multi-Task Transformer for Visual Scene Understanding
https://github.com/probcomp/threedp3
공식 코드https://github.com/prs-eth/marigold
공식 코드Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
https://github.com/public-bots/gaussianpretrain
공식 코드https://github.com/qiurui4shu/PIG
공식 코드https://github.com/qncsn2016/TR2
공식 코드Cross-Modality Time-Variant Relation Learning for Generating Dynamic Scene Graphs
https://github.com/qqqyd/visu
공식 코드Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing
https://github.com/qwtforgithub/cdsegnet
공식 코드https://github.com/r-seny/narrativexl
공식 코드NarrativeXL: A Large-scale Dataset For Long-Term Memory Models
https://github.com/rafa-cxg/PySGG-cxg
공식 코드Biasing Like Human: A Cognitive Bias Framework for Scene Graph Generation
https://github.com/raileye3d/raileye3d_dataset
공식 코드RGB-D Railway Platform Monitoring and Scene Understanding for Enhanced Passenger Safety
https://github.com/rajatkoner08/rtn
공식 코드https://github.com/rascalgdd/vpseg
공식 코드Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes
https://github.com/raymondwang987/nvds
공식 코드NVDS+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation
https://github.com/raysonlaroca/rodosol-alpr-dataset
공식 코드On the Cross-dataset Generalization in License Plate Recognition
https://github.com/rbler1234/ost-bench
공식 코드OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding
https://github.com/remcoroyen/vx-s3dis
공식 코드RESSCAL3D++: Joint Acquisition and Semantic Segmentation of 3D Point Clouds
https://github.com/renezurbruegg/icg_benchmark
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.