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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…
Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers
Sahil Bhandary Karnoor, Romit Roy Choudhury
Pose estimation refers to tracking a human's full body posture, including their head, torso, arms, and legs. The problem is challenging in practical settings where the number of bo…
Contrastive Diffusion Guidance for Spatial Inverse Problems
Sattwik Basu, Chaitanya Amballa, Zhongweiyang Xu +3
We consider a class of inverse problems characterized by forward operators that are partially specified, non-smooth, and non-differentiable. Although generative inverse solvers hav…
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…
Can NeRFs See without Cameras?
Chaitanya Amballa, Sattwik Basu, Yu-Lin Wei +3
Neural Radiance Fields (NeRFs) have been remarkably successful at synthesizing novel views of 3D scenes by optimizing a volumetric scene function. This scene function models how op…