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Spatial Reasoning
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ASMIftekhar/VSGNet
공식 코드VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions
https://github.com/CSU-JPG/MVPBench
공식 코드Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT
https://github.com/Chat-3D/Chat-3D
공식 코드Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes
https://github.com/CraftJarvis/ROCKET-1
공식 코드ROCKET-1: Mastering Open-World Interaction with Visual-Temporal Context Prompting
https://github.com/DoubtedSteam/MM-GCoT
공식 코드Grounded Chain-of-Thought for Multimodal Large Language Models
https://github.com/Earth-Intelligence-Lab/vleo-bench
공식 코드Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data
https://github.com/Fangjun-Li/SpatialLM-StepGame
공식 코드https://github.com/HLR/Dual-Action-VLN-CE
공식 코드https://github.com/HLR/FoREST
공식 코드FoREST: Frame of Reference Evaluation in Spatial Reasoning Tasks
https://github.com/HLR/SpartQA_generation
공식 코드SpartQA: : A Textual Question Answering Benchmark for Spatial Reasoning
https://github.com/JackHopkins/factorio-learning-environment
공식 코드https://github.com/JannerM/spatial-reasoning
공식 코드https://github.com/Jiaxuan-Li/MGU-Net
공식 코드https://github.com/Jirl-upenn/VLMnav
공식 코드https://github.com/MapEval/MapEval-API
공식 코드MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
https://github.com/MapEval/MapEval-Textual
공식 코드MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
https://github.com/MapEval/MapEval-Visual
공식 코드MapEval: A Map-Based Evaluation of Geo-Spatial Reasoning in Foundation Models
https://github.com/McGill-NLP/AURORA
공식 코드Learning Action and Reasoning-Centric Image Editing from Videos and Simulations
https://github.com/Neel1302/o1-planning-benchmark
공식 코드On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability
https://github.com/PierreMarza/teaching_agents_how_to_map
공식 코드Teaching Agents how to Map: Spatial Reasoning for Multi-Object Navigation
https://github.com/Pointcept/Pointcept
공식 코드Sonata: Self-Supervised Learning of Reliable Point Representations
https://github.com/RobBlackwell/can-llms-reason-about-the-rcc
공식 코드Can Large Language Models Reason about the Region Connection Calculus?
https://github.com/SPRIGHT-T2I/SPRIGHT
공식 코드Getting it Right: Improving Spatial Consistency in Text-to-Image Models
https://github.com/SharkyBamboozle/iVISPAR
공식 코드iVISPAR -- An Interactive Visual-Spatial Reasoning Benchmark for VLMs
https://github.com/THU-BPM/LLMArena
공식 코드LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments
https://github.com/TongZhangTHU/sgr
공식 코드A Universal Semantic-Geometric Representation for Robotic Manipulation
https://github.com/TonyLianLong/LLM-groundedDiffusion
공식 코드https://github.com/UCF-CRCV/ImplicitQA
공식 코드ImplicitQA: Going beyond frames towards Implicit Video Reasoning
https://github.com/VITA-Group/VLM-3R
공식 코드VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction
https://github.com/ZhengxiangShi/StepGame
공식 코드StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts
https://github.com/activevisionlab/awesome-llm-3d
공식 코드https://github.com/ai4ce/CityWalker
공식 코드CityWalker: Learning Embodied Urban Navigation from Web-Scale Videos
https://github.com/ai4ce/Contrastive-SPARE3D
공식 코드Self-supervised Spatial Reasoning on Multi-View Line Drawings
https://github.com/ai4ce/SPARE3D
공식 코드SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings
https://github.com/alanaai/evud
공식 코드AlanaVLM: A Multimodal Embodied AI Foundation Model for Egocentric Video Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.