3 citations · 8 across the 29 of their papers we have counts for
7 papers · 1 filter
Adaptive Adversarial Augmentation for Controllable Face Synthesis
Saransh Suri, Shivang Agarwal, Mayank Vatsa +1
Synthetic data provides a scalable alternative to real-world datasets for training face recognition models, particularly under challenging conditions such as low resolution, occlus…
Semantically Aligned Gradient-Driven Context-Preserving Image Editing
Chiranjeev Chiranjeev, Muskan Dosi, Mayank Vatsa +1
Instruction-guided image editing has a training-time blind spot. Generative editors are never required to semantically verify whether their outputs actually satisfy the instruction…
NumBench: Diagnosing Counting Failures in Text-to-Image Models
Sandeep Wadhwa, Mayank Vatsa, Richa Singh +2
Text-to-image (T2I) models often generate the wrong number of objects, yet existing benchmarks are too small or weakly controlled to explain why. We introduce \textbf{NumBench}, a…
CricRAG: Retrieval Augmented Vision-Language Models for Personalized Cricket Coaching
Agamdeep Singh, Sujit PB, Mayank Vatsa
Vision-Language Models (VLMs) offer promising capabilities for automated sports coaching but face a fundamental limitation: they implicitly compare against professional standards,…
Latent Performance Profiling of Large Language Models
Tanmoy Chakraborty, Ayan Sengupta, Suparna Bhattacharya +7
Large language models (LLMs) frequently achieve impressive scores on standardized benchmarks, yet accuracy alone offers a limited view of their capabilities. Evaluating open-source…
Unbiased Model Prediction Without Using Protected Attribute Information
Puspita Majumdar, Surbhi Mittal, Saheb Chhabra +2
The problem of bias persists in the deep learning community as models continue to provide disparate performance across different demographic subgroups. Therefore, several algorithm…
DivAS: Interactive 3D Segmentation by Depth-Weighted Voxel Aggregation
Ayush Pande, Mayank Vatsa
Interactive 3D segmentation of a reconstructed scene should not require a representation-specific optimization loop. We observe that the recipe for lifting 2D foundation-model mask…