Papers with Code 아카이브
Scene Parsing
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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/hailieqh/3d-object-primitive-graph
공식 코드Single Image 3D Object Estimation with Primitive Graph Networks
https://github.com/hanxunyu/inst3d-lmm
공식 코드Inst3D-LMM: Instance-Aware 3D Scene Understanding with Multi-modal Instruction Tuning
https://github.com/haochenheheda/SwiftNet
공식 코드https://github.com/haochenz11/iref-vla
공식 코드IRef-VLA: A Benchmark for Interactive Referential Grounding with Imperfect Language in 3D Scenes
https://github.com/happy-hsy/motionmae
공식 코드Self-supervised Video Representation Learning with Motion-Aware Masked Autoencoders
https://github.com/harboryuan/polyphonicformer
공식 코드PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation
https://github.com/harkiratbehl/MetaVOS
공식 코드Meta Learning Deep Visual Words for Fast Video Object Segmentation
https://github.com/harrytea/adaptvision
공식 코드AdaptVision: Dynamic Input Scaling in MLLMs for Versatile Scene Understanding
https://github.com/harrytea/root
공식 코드ROOT: VLM based System for Indoor Scene Understanding and Beyond
https://github.com/hashmatshadab/apr
공식 코드Adversarial Pixel Restoration as a Pretext Task for Transferable Perturbations
https://github.com/hasibzunair/rsud20k
공식 코드RSUD20K: A Dataset for Road Scene Understanding In Autonomous Driving
https://github.com/havrylovv/isegprobe
공식 코드Benchmarking Feature Upsampling Methods for Vision Foundation Models using Interactive Segmentation
https://github.com/hcplab-sysu/stket
공식 코드Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph Generation
https://github.com/hebeifast/eventlowlightvos
공식 코드https://github.com/helen1c/mc-panda
공식 코드https://github.com/heng-hw/spacap3d
공식 코드Spatiality-guided Transformer for 3D Dense Captioning on Point Clouds
https://github.com/henghuiding/MOSE-api
공식 코드MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
https://github.com/henghuiding/MeViS
공식 코드MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
https://github.com/hengliusky/few_shot_rvos
공식 코드Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples
https://github.com/hermannsblum/scim
공식 코드SCIM: Simultaneous Clustering, Inference, and Mapping for Open-World Semantic Scene Understanding
https://github.com/heshuting555/dshmp
공식 코드Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
https://github.com/hfslyc/GCPNet
공식 코드https://github.com/hhj1897/face_parsing
공식 코드RoI Tanh-polar Transformer Network for Face Parsing in the Wild
https://github.com/hhyhrhy/owmm-agent
공식 코드OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
https://github.com/hikopensource/davar-lab-ocr
공식 코드SPIN: Structure-Preserving Inner Offset Network for Scene Text Recognition
https://github.com/hiltonml/camera_trap_tools
공식 코드An Image Processing Pipeline for Camera Trap Time-Lapse Recordings
https://github.com/hitcslj/ssd
공식 코드Stealing Stable Diffusion Prior for Robust Monocular Depth Estimation
https://github.com/hithqd/unim-ov3d
공식 코드https://github.com/hitottiez/sdof-tracker
공식 코드SDOF-Tracker: Fast and Accurate Multiple Human Tracking by Skipped-Detection and Optical-Flow
https://github.com/hkchengrex/CascadePSP
공식 코드https://github.com/hkchengrex/Cutie
공식 코드https://github.com/hkchengrex/MiVOS
공식 코드https://github.com/hkchengrex/STCN
공식 코드Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
https://github.com/hkchengrex/Tracking-Anything-with-DEVA
공식 코드https://github.com/hkchengrex/XMem
공식 코드XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.