activity
20232026
collaborators

6 papers

cs.CV2026

Unsupervised Detection of Entry and Exit Regions from Vehicle Trajectories for Camera-Agnostic Turning Movement Counts

Parikshit Singh Rathore, Vishwajeet Pattanaik, Punit Rathore

Turning movement counts are essential for intersection-level traffic management, yet their collection remains predominantly manual due to the cost of per-camera region annotation.…

cs.CV2026

BMD-45: A Large-Scale CCTV Vehicle Detection Dataset for Urban Traffic in Developing Cities

Akash Sharma, Chinmay Mhatre, Sankalp Gawali +8

Robust vehicle detection from fixed CCTV cameras is critical for Intelligent Transportation Systems. Yet existing benchmarks predominantly feature relatively homogeneous, highly or…

cs.CV2025

The Urban Vision Hackathon Dataset and Models: Towards Image Annotations and Accurate Vision Models for Indian Traffic

Akash Sharma, Chinmay Mhatre, Sankalp Gawali +10

This report describes the UVH-26 dataset, the first public release by AIM@IISc of a large-scale dataset of annotated traffic-camera images from India. The dataset comprises 26,646…

eess.IV2024

A Visual-Analytical Approach for Automatic Detection of Cyclonic Events in Satellite Observations

Akash Agrawal, Mayesh Mohapatra, Abhinav Raja +5

Estimating the location and intensity of tropical cyclones holds crucial significance for predicting catastrophic weather events. In this study, we approach this task as a detectio…

cs.LG2023

Learning Low-Rank Latent Spaces with Simple Deterministic Autoencoder: Theoretical and Empirical Insights

Alokendu Mazumder, Tirthajit Baruah, Bhartendu Kumar +3

The autoencoder is an unsupervised learning paradigm that aims to create a compact latent representation of data by minimizing the reconstruction loss. However, it tends to overloo…

cs.LG2023

DeepVAT: A Self-Supervised Technique for Cluster Assessment in Image Datasets

Alokendu Mazumder, Tirthajit Baruah, Akash Kumar Singh +3

Estimating the number of clusters and cluster structures in unlabeled, complex, and high-dimensional datasets (like images) is challenging for traditional clustering algorithms. In…