Visual Navigation

101 papers with code • 6 benchmarks • 16 datasets

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

Libraries

Use these libraries to find Visual Navigation models and implementations

TTA-Nav: Test-time Adaptive Reconstruction for Point-Goal Navigation under Visual Corruptions

maytusp/tta-nav 4 Mar 2024

Our "plug-and-play" method incorporates a top-down decoder to a pre-trained navigation model.

1
04 Mar 2024

MemoNav: Working Memory Model for Visual Navigation

zjulihongxin/memonav 29 Feb 2024

Subsequently, a graph attention module encodes the retained STM and the LTM to generate working memory (WM) which contains the scene features essential for efficient navigation.

2
29 Feb 2024

Towards Learning a Generalist Model for Embodied Navigation

zd11024/NaviLLM 4 Dec 2023

We conduct extensive experiments to evaluate the performance and generalizability of our model.

58
04 Dec 2023

What you see is what you get: Experience ranking with deep neural dataset-to-dataset similarity for topological localisation

mttgdd/vdna-experience-selection 20 Oct 2023

In the case of localisation, important dataset differences impacting performance are modes of appearance change, including weather, lighting, and season.

3
20 Oct 2023

Zero-Shot Object Goal Visual Navigation With Class-Independent Relationship Network

smartandcleverrobot/icra-cirn 15 Oct 2023

This method combines target detection information with the relative semantic similarity between the target and the navigation target, and constructs a brand new state representation based on similarity ranking, this state representation does not include target feature or environment feature, effectively decoupling the agent's navigation ability from target features.

0
15 Oct 2023

CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes

polkalian/internav 21 Sep 2023

Visual navigation has been widely studied under the assumption that there may be several clear routes to reach the goal.

0
21 Sep 2023

CaMP: Causal Multi-policy Planning for Interactive Navigation in Multi-room Scenes

polkalian/internav NeurIPS 2023

Visual navigation has been widely studied under the assumption that there may be several clear routes to reach the goal.

0
21 Sep 2023

VLN-PETL: Parameter-Efficient Transfer Learning for Vision-and-Language Navigation

yanyuanqiao/vln-petl ICCV 2023

The performance of the Vision-and-Language Navigation~(VLN) tasks has witnessed rapid progress recently thanks to the use of large pre-trained vision-and-language models.

5
20 Aug 2023

Language-enhanced RNR-Map: Querying Renderable Neural Radiance Field maps with natural language

intelligolabs/Le-RNR-Map 17 Aug 2023

We present Le-RNR-Map, a Language-enhanced Renderable Neural Radiance map for Visual Navigation with natural language query prompts.

13
17 Aug 2023

Scaling Data Generation in Vision-and-Language Navigation

wz0919/scalevln ICCV 2023

Recent research in language-guided visual navigation has demonstrated a significant demand for the diversity of traversable environments and the quantity of supervision for training generalizable agents.

129
28 Jul 2023