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20242026
most citedRevisit Anything: Visual Place Recognition via Image Segment Retrieval

1 citations · 2 across the 7 of their papers we have counts for

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cs.CV2026

SILICA: Repurposing Diffusion Priors for Joint Glass Segmentation and Depth Estimation

Tarun R, Anuj Verma, Laksh Nanwani +2

Standard depth sensors systematically fail on transparent surfaces, creating corrupted 3D maps and severe navigation hazards. While specialized hardware sensors can detect glass, t…

cs.CV2025

SceneEdited: A City-Scale Benchmark for 3D HD Map Updating via Image-Guided Change Detection

Chun-Jung Lin, Tat-Jun Chin, Sourav Garg +1

Accurate, up-to-date High-Definition (HD) maps are critical for urban planning, infrastructure monitoring, and autonomous navigation. However, these maps quickly become outdated as…

cs.CV2025

SegMASt3R: Geometry Grounded Segment Matching

Rohit Jayanti, Swayam Agrawal, Vansh Garg +4

Segment matching is an important intermediate task in computer vision that establishes correspondences between semantically or geometrically coherent regions across images. Unlike…

cs.CV20241 cited

Revisit Anything: Visual Place Recognition via Image Segment Retrieval

Kartik Garg, Sai Shubodh Puligilla, Shishir Kolathaya +2

Accurately recognizing a revisited place is crucial for embodied agents to localize and navigate. This requires visual representations to be distinct, despite strong variations in…

cs.CV2024

Robust Scene Change Detection Using Visual Foundation Models and Cross-Attention Mechanisms

Chun-Jung Lin, Sourav Garg, Tat-Jun Chin +1

We present a novel method for scene change detection that leverages the robust feature extraction capabilities of a visual foundational model, DINOv2, and integrates full-image cro…

cs.CV2024

QueSTMaps: Queryable Semantic Topological Maps for 3D Scene Understanding

Yash Mehan, Kumaraditya Gupta, Rohit Jayanti +3

Robotic tasks such as planning and navigation require a hierarchical semantic understanding of a scene, which could include multiple floors and rooms. Current methods primarily foc…