50 citations · 96 across the 8 of their papers we have counts for
8 papers
ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation
Anindya Mondal, Sauradip Nag, Anjan Dutta
We present ABACUS, a unified vision-language model that jointly addresses object counting, crowd counting, referring-expression counting, and count-faithful image generation within…
CountLoop: Training-Free High-Instance Image Generation via Iterative Agent Guidance
Anindya Mondal, Ayan Banerjee, Sauradip Nag +3
Diffusion models excel at photorealistic synthesis but struggle with object count fidelity, especially in high-density settings. We introduce COUNTLOOP, a training-free framework t…
OmniCount: Multi-label Object Counting with Semantic-Geometric Priors
Anindya Mondal, Sauradip Nag, Xiatian Zhu +1
Object counting is pivotal for understanding the composition of scenes. Previously, this task was dominated by class-specific methods, which have gradually evolved into more adapta…
Actor-agnostic Multi-label Action Recognition with Multi-modal Query
Anindya Mondal, Sauradip Nag, Joaquin M Prada +2
Existing action recognition methods are typically actor-specific due to the intrinsic topological and apparent differences among the actors. This requires actor-specific pose estim…
Time-varying Signals Recovery via Graph Neural Networks
Jhon A. Castro-Correa, Jhony H. Giraldo, Anindya Mondal +3
The recovery of time-varying graph signals is a fundamental problem with numerous applications in sensor networks and forecasting in time series. Effectively capturing the spatio-t…
Recovery of Missing Sensor Data by Reconstructing Time-varying Graph Signals
Anindya Mondal, Mayukhmali Das, Aditi Chatterjee +1
Wireless sensor networks are among the most promising technologies of the current era because of their small size, lower cost, and ease of deployment. With the increasing number of…
Moving Object Detection for Event-based vision using Graph Spectral Clustering
Anindya Mondal, Shashant R, Jhony H. Giraldo +2
Moving object detection has been a central topic of discussion in computer vision for its wide range of applications like in self-driving cars, video surveillance, security, and en…
Moving Object Detection for Event-based Vision using k-means Clustering
Anindya Mondal, Mayukhmali Das
Moving object detection is important in computer vision. Event-based cameras are bio-inspired cameras that work by mimicking the working of the human eye. These cameras have multip…