SOTAVerified

Visual Navigation

Visual Navigation is the problem of navigating an agent, e.g. a mobile robot, in an environment using camera input only. The agent is given a target image (an image it will see from the target position), and its goal is to move from its current position to the target by applying a sequence of actions, based on the camera observations only.

Source: Vision-based Navigation Using Deep Reinforcement Learning

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 316 papers

TitleStatusHype
DRISHTI: Visual Navigation Assistant for Visually Impaired—0
Learning and Planning with a Semantic Model—0
IN-Sight: Interactive Navigation through Sight—0
Learned Camera Gain and Exposure Control for Improved Visual Feature Detection and Matching—0
Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation—0
Learning On-Road Visual Control for Self-Driving Vehicles with Auxiliary Tasks—0
Invariance is Key to Generalization: Examining the Role of Representation in Sim-to-Real Transfer for Visual Navigation—0
Integrating Symmetry into Differentiable Planning with Steerable Convolutions—0
DeepRelativeFusion: Dense Monocular SLAM using Single-Image Relative Depth Prediction—0
Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances—0
Initialization of Monocular Visual Navigation for Autonomous Agents Using Modified Structure from Small Motion—0
Deep Learning for Visual Navigation of Underwater Robots—0
Improving Visual Feature Extraction in Glacial Environments—0
Improving Vision-and-Language Navigation by Generating Future-View Image Semantics—0
Deep Learning for Embodied Vision Navigation: A Survey—0
Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks—0
Approximate Inverse Reinforcement Learning from Vision-based Imitation Learning—0
Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation—0
Adaptive Navigation Scheme for Optimal Deep-Sea Localization Using Multimodal Perception Cues—0
Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge—0
Improving the Generalization of Visual Navigation Policies using Invariance Regularization—0
Learned Visual Navigation for Under-Canopy Agricultural Robots—0
Improving Target-driven Visual Navigation with Attention on 3D Spatial Relationships—0
Learning a State Representation and Navigation in Cluttered and Dynamic Environments—0
Decision-based AI Visual Navigation for Cardiac Ultrasounds—0
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All datasetsCooperative Vision-and-Dialogue NavigationR2RSOON TestAI2-THORDmlab-30Help, Anna! (HANNA)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NaviLLMdist_to_end_reduction7.9—Unverified
2VLN-PETLdist_to_end_reduction6.13—Unverified
3early to beddist_to_end_reduction6.03—Unverified
4HAMTdist_to_end_reduction5.58—Unverified
5s-agent (NDH-Full)dist_to_end_reduction5.27—Unverified
6BabyWalk (r2r-pretrain)dist_to_end_reduction4.46—Unverified
7Environment-agnostic Multitask Learningdist_to_end_reduction3.91—Unverified
8BabyWalkdist_to_end_reduction3.65—Unverified
9Test2-NDHdist_to_end_reduction3.44—Unverified
10SCoAdist_to_end_reduction3.37—Unverified
#ModelMetricClaimedVerifiedStatus
1SUSAspl0.64—Unverified
2Meta-Explorespl0.61—Unverified
3NaviLLMspl0.6—Unverified
4BEV-BERTspl0.6—Unverified
5HOPspl0.59—Unverified
6DUETspl0.58—Unverified
7VLN-PETLspl0.58—Unverified
8VLN-BERTspl0.57—Unverified
9Prevalentspl0.51—Unverified
10RCM+SIL(no early exploration)spl0.38—Unverified
#ModelMetricClaimedVerifiedStatus
1AutoVLNNav-SPL27.83—Unverified
2NaviLLMNav-SPL26.26—Unverified
3Meta-ExploreNav-SPL25.8—Unverified
4SUSANav-SPL25.47—Unverified
5DUETNav-SPL21.42—Unverified
6GBENav-SPL13.3—Unverified
#ModelMetricClaimedVerifiedStatus
1MVV-INSPL (All)17.27—Unverified
2SAVNSPL (All)16.15—Unverified
#ModelMetricClaimedVerifiedStatus
1PopArt-IMPALAMedium Human-Normalized Score72.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Prevalentspl28.72—Unverified