Projects

Selected work on large-scale training, generative models and multimodal learning.

18 peer-reviewed publications

Research internships at Google · NVIDIA · Adobe · MERL

Publications

9 research projects

CVPR 2025

GenDeg

A diffusion model creates degraded versions of clean images, giving restoration models more varied examples to learn from.

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CVPR 2023

Unite and Conquer

Generate images from combinations of text, class labels, semantic maps and sketches. Models learn each condition separately and combine them during sampling.

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ICCV 2023

Steered Diffusion

Guide a pretrained image generator to restore images or follow new conditions, without training a separate generator for each task.

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ECCV 2024

MaxFusion

Combine controls such as pose, depth and scene layout so they can guide the same image, even when parts of the controls disagree.

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Accepted to WACV 2027

Scale-Wise VAR

Show how a particular scale-by-scale image generator can behave like a diffusion model, allowing it to refine its predictions.

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WACV Oral 2025

PETALface

Adapt a strong face-recognition model to degraded images by training small quality-dependent adapters instead of the entire backbone.

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CVPR 2024

CrowdDiff

Generate several possible crowd maps and combine their head detections to reduce counting errors in dense or ambiguous scenes.

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Internships

Adobe · May – Aug 2023

Control2Control

I worked on Control2Control during my Adobe internship. The project uses sketches, poses and layouts to edit an image while helping preserve the surrounding scene.

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MERL · May – Aug 2022

Steered Diffusion

Guide a pretrained image generator to restore images or follow new conditions, without training a separate generator for each task.

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Special thanks to Codex for helping create this Projects section.