most citedSteering Rectified Flow Models in the Vector Field for Controlled Image Generation

1 citations · 1 across the 3 of their papers we have counts for

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5 papers

cs.CV2025

AutoEdit: Automatic Hyperparameter Tuning for Image Editing

Chau Pham, Quan Dao, Mahesh Bhosale +3

Recent advances in diffusion models have revolutionized text-guided image editing, yet existing editing methods face critical challenges in hyperparameter identification. To get th…

cs.CV2025

Discrete Noise Inversion for Next-scale Autoregressive Text-based Image Editing

Quan Dao, Xiaoxiao He, Ligong Han +6

Visual autoregressive models (VAR) have recently emerged as a promising class of generative models, achieving performance comparable to diffusion models in text-to-image generation…

cs.CV2024

Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction

Shiyu Zhao, Zhenting Wang, Felix Juefei-Xu +7

Prevailing Multimodal Large Language Models (MLLMs) encode the input image(s) as vision tokens and feed them into the language backbone, similar to how Large Language Models (LLMs)…

cs.CV20241 cited

Steering Rectified Flow Models in the Vector Field for Controlled Image Generation

Maitreya Patel, Song Wen, Dimitris N. Metaxas +1

Diffusion models (DMs) excel in photorealism, image editing, and solving inverse problems, aided by classifier-free guidance and image inversion techniques. However, rectified flow…

cs.CV2024

DiMSUM: Diffusion Mamba -- A Scalable and Unified Spatial-Frequency Method for Image Generation

Hao Phung, Quan Dao, Trung Dao +3

We introduce a novel state-space architecture for diffusion models, effectively harnessing spatial and frequency information to enhance the inductive bias towards local features in…