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Vision-Language Navigation
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Vision-language navigation (VLN) is the task of navigating an embodied agent to carry out natural language instructions inside real 3D environments.
<span style="color:grey; opacity: 0.6">( Image credit: Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/huggingface/lerobot
공식 코드SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
https://github.com/huixin-zhan-ai/surgeon_style_fingerprinting
공식 코드https://github.com/jialuli-luka/SyntaxVLN
공식 코드Improving Cross-Modal Alignment in Vision Language Navigation via Syntactic Information
https://github.com/jialuli-luka/clear
공식 코드CLEAR: Improving Vision-Language Navigation with Cross-Lingual, Environment-Agnostic Representations
https://github.com/jiaming-zhou/X-ICM
공식 코드Exploring the Limits of Vision-Language-Action Manipulations in Cross-task Generalization
https://github.com/joeyy5588/planning-as-inpainting
공식 코드https://github.com/johnsonjiang1996/awesome-vla4ad
공식 코드A Survey on Vision-Language-Action Models for Autonomous Driving
https://github.com/lcfractal/vlnrem
공식 코드https://github.com/lcysyzxdxc/embodiediqa
공식 코드https://github.com/liangcici/CITL-VLN
공식 코드Contrastive Instruction-Trajectory Learning for Vision-Language Navigation
https://github.com/liangcici/probes-vln
공식 코드Visual-Language Navigation Pretraining via Prompt-based Environmental Self-exploration
https://github.com/lostxine/llara
공식 코드LLaRA: Supercharging Robot Learning Data for Vision-Language Policy
https://github.com/marsaki/etpnav
공식 코드ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments
https://github.com/mint-sjtu/robofac
공식 코드RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction
https://github.com/mrzihan/hnr-vln
공식 코드Lookahead Exploration with Neural Radiance Representation for Continuous Vision-Language Navigation
https://github.com/muhayyuddin/vlas
공식 코드Vision Language Action Models in Robotic Manipulation: A Systematic Review
https://github.com/opendrivelab/univla
공식 코드UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
https://github.com/peteanderson80/Matterport3DSimulator
공식 코드https://github.com/pickxiguapi/embodied-fsd
공식 코드From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
https://github.com/rossgreer/doscenes
공식 코드https://github.com/sadil13/vln-ram
공식 코드https://github.com/sautenich/uav-vla
공식 코드UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission Generation
https://github.com/showlab/showui
공식 코드ShowUI: One Vision-Language-Action Model for GUI Visual Agent
https://github.com/sled-group/danli
공식 코드DANLI: Deliberative Agent for Following Natural Language Instructions
https://github.com/tutujingyugang1/ChatVLA_public
공식 코드ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model
https://github.com/ucla-mobility/AutoVLA
공식 코드https://github.com/ustcwhy/bitvla
공식 코드BitVLA: 1-bit Vision-Language-Action Models for Robotics Manipulation
https://github.com/waynemao/robomatrix
공식 코드https://github.com/william-wang618/roboticattack
공식 코드Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics
https://github.com/yuankaiqi/orist
공식 코드https://github.com/yueen-ma/awesome-vla
공식 코드https://github.com/yueyang130/deer-vla
공식 코드DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution
https://github.com/yushengzhao/td-stp
공식 코드Target-Driven Structured Transformer Planner for Vision-Language Navigation
https://github.com/zzxslp/Bilingual-VLN
공식 코드https://github.com/zzxslp/Crosslingual-VLN
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.