18 papers
Explicit Context-Driven Neural Acoustic Modeling for High-Fidelity RIR Generation
Chen Si, Qianyi Wu, Chaitanya Amballa +1
Realistic sound simulation plays a critical role in many applications. A key element in sound simulation is the room impulse response (RIR), which characterizes how sound propagate…
TILT: Improving Compositional Generation in Diffusion Models with a Model-Intrinsic Reward
Debottam Dutta, Jaehoon Hahm, Jianchong Chen +1
Recent advances in powerful text-to-image generation models have made it increasingly important to develop test-time methods that modify the sampling trajectory to produce images m…
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…
Discrete Langevin-Inspired Posterior Sampling
Chaitanya Amballa, Sattwik Basu, Jorge VanÄo Sampedro +1
We study posterior sampling for inverse problems in discrete state spaces using discrete diffusion models as generative priors. While continuous diffusion models have become widely…
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…
Unified Diffusion Refinement for Multi-Channel Speech Enhancement and Separation
Zhongweiyang Xu, Ashutosh Pandey, Juan Azcarreta +4
We propose Uni-ArrayDPS, a novel diffusion-based refinement framework for unified multi-channel speech enhancement and separation. Existing methods for multi-channel speech enhance…