Papers with Code 아카이브

Scene Understanding

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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://bitbucket.org/deeplabai/vrd

공식 코드

Deeply Supervised Multimodal Attentional Translation Embeddings for Visual Relationship Detection

https://github.com/0liliulei/mask-vos

공식 코드

Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation

https://github.com/18979705623/hspr

공식 코드

Hierarchical Spatial Proximity Reasoning for Vision-and-Language Navigation

https://github.com/3dlg-hcvc/M3DRef-CLIP

공식 코드

Multi3DRefer: Grounding Text Description to Multiple 3D Objects

https://github.com/4dvlab/hucenlife

공식 코드

Human-centric Scene Understanding for 3D Large-scale Scenarios

https://github.com/594422814/ContrastCorr

공식 코드

Contrastive Transformation for Self-supervised Correspondence Learning

https://github.com/983632847/awesome-multimodal-object-tracking

공식 코드

Underwater Camouflaged Object Tracking Meets Vision-Language SAM2

https://github.com/AIS-Bonn/synpick

공식 코드

SynPick: A Dataset for Dynamic Bin Picking Scene Understanding

https://github.com/AKASH2907/End-to-End-Semi-Supervised-Learning-for-Video-Action-Detection

공식 코드

End-to-End Semi-Supervised Learning for Video Action Detection

https://github.com/AKASH2907/stable-mean-teacher

공식 코드

Stable Mean Teacher for Semi-supervised Video Action Detection

https://github.com/AVC2-UESTC/OV2VSS

공식 코드

Towards Open-Vocabulary Video Semantic Segmentation

https://github.com/AbanobSoliman/IBISCape

공식 코드

IBISCape: A Simulated Benchmark for multi-modal SLAM Systems Evaluation in Large-scale Dynamic Environments

https://github.com/Ali2500/HODOR

공식 코드

HODOR: High-level Object Descriptors for Object Re-segmentation in Video Learned from Static Images

https://github.com/Ali2500/TarViS

공식 코드

TarViS: A Unified Approach for Target-based Video Segmentation

https://github.com/Andreas-Pfeuffer/LSTM-ICNet

공식 코드

Robust Semantic Segmentation in Adverse Weather Conditions by means of Fast Video-Sequence Segmentation

https://github.com/AngeLouCN/SAM-2_Surgical_Video

공식 코드

Zero-Shot Surgical Tool Segmentation in Monocular Video Using Segment Anything Model 2

https://github.com/AnshShah3009/MetricGold

공식 코드

MetricGold: Leveraging Text-To-Image Latent Diffusion Models for Metric Depth Estimation

https://github.com/AutoCompSysLab/DCTNet

공식 코드

A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View

https://github.com/Bravo5542/TJSTG

공식 코드

Target-Aware Spatio-Temporal Reasoning via Answering Questions in Dynamics Audio-Visual Scenarios

https://github.com/BryanPlummer/pl-clc

공식 코드

Phrase Localization and Visual Relationship Detection with Comprehensive Image-Language Cues

https://github.com/ByungKwanLee/MoAI

공식 코드

MoAI: Mixture of All Intelligence for Large Language and Vision Models

https://github.com/CSAILVision/unifiedparsing

공식 코드

Unified Perceptual Parsing for Scene Understanding

https://github.com/CVLAB-Unibo/omeganet

공식 코드

Distilled Semantics for Comprehensive Scene Understanding from Videos

https://github.com/CXH-Research/DHAN-SHR

공식 코드

Dual-Hybrid Attention Network for Specular Highlight Removal

https://github.com/Cadene/block.bootstrap.pytorch

공식 코드

BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

https://github.com/Cavendish518/LE-Nav

공식 코드

Learning to Tune Like an Expert: Interpretable and Scene-Aware Navigation via MLLM Reasoning and CVAE-Based Adaptation

https://github.com/Chat-3D/Chat-3D

공식 코드

Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes

https://github.com/Chenyang-Lu/semantic-foreground-inpainting

공식 코드

Semantic Foreground Inpainting from Weak Supervision

https://github.com/Danial-Qashqai/CSFNet

공식 코드

CSFNet: A Cosine Similarity Fusion Network for Real-Time RGB-X Semantic Segmentation of Driving Scenes

https://github.com/Dayan-Guan/DA-VSN

공식 코드

Domain Adaptive Video Segmentation via Temporal Consistency Regularization

https://github.com/DiffusionLight/DiffusionLight

공식 코드

DiffusionLight: Light Probes for Free by Painting a Chrome Ball

https://github.com/DirtyHarryLYL/HAKE-Action-Torch

공식 코드

HAKE: A Knowledge Engine Foundation for Human Activity Understanding

https://github.com/DriveVLA/OpenDriveVLA

공식 코드

OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model

https://github.com/Earth-Intelligence-Lab/vleo-bench

공식 코드

Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data

https://github.com/EmbodiedVision/cosection

공식 코드

Where Does It End? -- Reasoning About Hidden Surfaces by Object Intersection Constraints

https://github.com/GAP-LAB-CUHK-SZ/SAMPro3D

공식 코드

SAMPro3D: Locating SAM Prompts in 3D for Zero-Shot Scene Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.