6 papers
Dependency-Aware Discrete Diffusion for Scene Graph Generation
Rajalaxmi Rajagopalan, Romit Roy Choudhury
Scene graphs (SGs) represent objects and their relationships as structured graphs, enabling applications in image generation, robotics, and 3D understanding. Recent work suggests t…
Personalized Image Generation via Human-in-the-loop Bayesian Optimization
Rajalaxmi Rajagopalan, Debottam Dutta, Yu-Lin Wei +1
Imagine Alice has a specific image in her mind, say, the view of the street in which she grew up during her childhood. To generate that exact image, she guides a generativ…
Masked Autoencoders as Universal Speech Enhancer
Rajalaxmi Rajagopalan, Ritwik Giri, Zhiqiang Tang +1
Supervised speech enhancement methods have been very successful. However, in practical scenarios, there is a lack of clean speech, and self-supervised learning-based (SSL) speech e…
Steer Away From Mode Collisions: Improving Composition In Diffusion Models
Debottam Dutta, Jianchong Chen, Rajalaxmi Rajagopalan +2
We propose to improve multi-concept prompt fidelity in text-to-image diffusion models. We begin with common failure cases - prompts like "a cat and a dog" that sometimes yields ima…
Kernel Learning for Sample Constrained Black-Box Optimization
Rajalaxmi Rajagopalan, Yu-Lin Wei, Romit Roy Choudhury
Black box optimization (BBO) focuses on optimizing unknown functions in high-dimensional spaces. In many applications, sampling the unknown function is expensive, imposing a tight…
Sample-Constrained Black Box Optimization for Audio Personalization
Rajalaxmi Rajagopalan, Yu-Lin Wei, Romit Roy Choudhury
We consider the problem of personalizing audio to maximize user experience. Briefly, we aim to find a filter , which applied to any music or speech, will maximize the user's s…