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cs.CV2026

Do-Undo Bench: Reversibility for Action Understanding in Image Generation

Shweta Mahajan, Shreya Kadambi, Hoang Le +4

We introduce the Do-Undo task and benchmark to address a critical gap in vision-language models: understanding and generating plausible scene transformations driven by real-world a…

cs.CV2026

MultiHuman-Testbench: Benchmarking Image Generation for Multiple Humans

Shubhankar Borse, Seokeon Choi, Sunghyun Park +6

Generation of images containing multiple humans, performing complex actions, while preserving their facial identities, is a significant challenge. A major factor contributing to th…

cs.CV2025

MADI: Masking-Augmented Diffusion with Inference-Time Scaling for Visual Editing

Shreya Kadambi, Risheek Garrepalli, Shubhankar Borse +2

Despite the remarkable success of diffusion models in text-to-image generation, their effectiveness in grounded visual editing and compositional control remains challenging. Motiva…

cs.CV2025

SubZero: Composing Subject, Style, and Action via Zero-Shot Personalization

Shubhankar Borse, Kartikeya Bhardwaj, Mohammad Reza Karimi Dastjerdi +8

Diffusion models are increasingly popular for generative tasks, including personalized composition of subjects and styles. While diffusion models can generate user-specified subjec…

cs.CV2024

FouRA: Fourier Low Rank Adaptation

Shubhankar Borse, Shreya Kadambi, Nilesh Prasad Pandey +7

While Low-Rank Adaptation (LoRA) has proven beneficial for efficiently fine-tuning large models, LoRA fine-tuned text-to-image diffusion models lack diversity in the generated imag…