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Aditya Patel

3 accepted papers

2026

Scaling Zero-Shot Reference-to-Video Generation

CVPR 2026

Reference-to-video (R2V) generation aims to synthesize videos that align with a text prompt while preserving the subject identity from reference images. However, current R2V methods are hindered by the reliance on explicit reference image-video-text triplets, whose construction is highly expensive a

Cited by 0SourcecodeScholar
2026

TUNA: Taming Unified Visual Representations for Native Unified Multimodal Models

CVPR 2026

Unified multimodal models (UMMs) aim to jointly perform multimodal understanding and generation within a single framework. We present TUNA, a native UMM that builds a unified continuous visual representation by cascading a VAE encoder with a representation encoder. This unified representation space

Cited by 0SourceScholar
2025

Learning Flow Fields in Attention for Controllable Person Image Generation

CVPR 2025poster

Controllable person image generation aims to generate a person image conditioned on reference images, allowing precise control over the person's appearance or pose.However, prior methods often distort fine-grained textural details from the reference image, despite achieving high overall image qualit…