80 citations · 165 across the 15 of their papers we have counts for
15 papers
PixelUp: Zero-Shot Semantic Feature Upsampling for Fine-Grained Vision Tasks
Deepank Singh, Anurag Nihal, Vedhus Hoskere
Self-supervised Vision Foundation Models (VFMs) have become essential backbones for downstream tasks due to their strong and transferable visual representations. However, their pat…
Excite, Attend and Segment (EASe): Domain-Agnostic Fine-Grained Mask Discovery with Feature Calibration and Self-Supervised Upsampling
Deepank Singh, Anurag Nihal, Vedhus Hoskere
Unsupervised segmentation approaches have increasingly leveraged foundation models (FM) to improve salient object discovery. However, these methods often falter in scenes with comp…
RAGalyst: Automated Human-Aligned Agentic Evaluation for Domain-Specific RAG
Joshua Gao, Quoc Huy Pham, Subin Varghese +2
Retrieval-Augmented Generation (RAG) is a critical technique for grounding Large Language Models (LLMs) in factual evidence, yet evaluating RAG systems in specialized, safety-criti…
BridgeEQA: Virtual Embodied Agents for Real Bridge Inspections
Subin Varghese, Joshua Gao, Asad Ur Rahman +1
Deploying embodied agents that can answer questions about their surroundings in realistic real-world settings remains difficult, partly due to the scarcity of benchmarks for episod…
ViewDelta: Scaling Scene Change Detection through Text-Conditioning
Subin Varghese, Joshua Gao, Vedhus Hoskere
We introduce a generalized framework for Scene Change Detection (SCD) that addresses the core ambiguity of distinguishing "relevant" from "nuisance" changes, enabling effective joi…
Multiclass Post-Earthquake Building Assessment Integrating High-Resolution Optical and SAR Satellite Imagery, Ground Motion, and Soil Data with Transformers
Deepank Singh, Vedhus Hoskere, Pietro Milillo
Timely and accurate assessments of building damage are crucial for effective response and recovery in the aftermath of earthquakes. Conventional preliminary damage assessments (PDA…
Instance Segmentation of Reinforced Concrete Bridges with Synthetic Point Clouds
Asad Ur Rahman, Vedhus Hoskere
The National Bridge Inspection Standards require detailed element-level bridge inspections. Traditionally, inspectors manually assign condition ratings by rating structural compone…
Vision-Based Adaptive Robotics for Autonomous Surface Crack Repair
Joshua Genova, Eric Cabrera, Vedhus Hoskere
Surface cracks in infrastructure can lead to severe deterioration and expensive maintenance if not efficiently repaired. Manual repair methods are labor-intensive, time-consuming,…
View-Invariant Pixelwise Anomaly Detection in Multi-object Scenes with Adaptive View Synthesis
Subin Varghese, Vedhus Hoskere
The built environment, encompassing critical infrastructure such as bridges and buildings, requires diligent monitoring of unexpected anomalies or deviations from a normal state in…
Deep Learning Hydrodynamic Forecasting for Flooded Region Assessment in Near-Real-Time (DL Hydro-FRAN)
Francisco Haces-Garcia, Natalya Maslennikova, Craig L Glennie +3
Hydrodynamic flood modeling improves hydrologic and hydraulic prediction of storm events. However, the computationally intensive numerical solutions required for high-resolution hy…
Towards Automated Post-Earthquake Inspections with Deep Learning-based Condition-Aware Models
Vedhus Hoskere, Yasutaka Narazaki, Tu A. Hoang +1
In the aftermath of an earthquake, rapid structural inspections are required to get citizens back in to their homes and offices in a safe and timely manner. These inspections gfare…
Automated Bridge Component Recognition using Video Data
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
This paper investigates the automated recognition of structural bridge components using video data. Although understanding video data for structural inspections is straightforward…
Automated Vision-based Bridge Component Extraction Using Multiscale Convolutional Neural Networks
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
Image data has a great potential of helping post-earthquake visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing v…
Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding
Yasutaka Narazaki, Vedhus Hoskere, Tu A. Hoang +1
Image data has a great potential of helping conventional visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visu…
Vision-based Structural Inspection using Multiscale Deep Convolutional Neural Networks
Vedhus Hoskere, Yasutaka Narazaki, Tu Hoang +1
Current methods of practice for inspection of civil infrastructure typically involve visual assessments conducted manually by trained inspectors. For post-earthquake structural ins…