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ICML2025Top-tier venue

FlexControl: Computation-Aware Conditional Control with Differentiable Router for Text-to-Image Generation

Zheng Fang, Lichuan Xiang, Xu Cai, Kaicheng Zhou, Hongkai Wen

Abstract

Figure 1. Dynamically inject conditional controls for image generation based on timestep and task-specific sample. (a) The architecture of conventional controllable generative model -ControlNet. (b) The architecture of the proposed FlexControl. (c) Statistics on the number of activated control blocks of the FlexControl at each denoising step. Here, "∼50% spasity" indicates that the number of floating-point operations (FLOPs) of activated blocks is limited to 50% of the trainable branch.

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Cited by top-tier papers3

  1. Accelerating Diffusion Model Training under Minimal Budgets: A Condensation-Based PerspectiveRui Huang, Shitong Shao, Zikai Zhou, Pukun Zhao et al.CVPR 2026 · 7 citations
  2. Steering Where to Diffuse: Generative Modeling of Phenotypic Response Simulation with Steered Diffusion BridgeRongchao Zhang, Chengxin Li, Yiwei Lou, Yuling Shi et al.CVPR 2026 · 1 citation
  3. DynFusion: Rethinking Condition Fusion for Adaptive Multi-Conditional Text-to-Image GenerationZheng Fang, Lichuan Xiang, Xu Cai, Bing Wang et al.CVPR 2026

Builds on33

  1. Learning Transferable Visual Models From Natural Language SupervisionAlec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh et al.ICML 2021 · 47,906 citations
  2. Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 35,902 citations
  3. Diffusion Models Beat GANs on Image SynthesisPrafulla Dhariwal, Alexander Quinn NicholNeurIPS 2021 · 13,211 citations
  4. High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser et al.CVPR 2022 · 13,123 citations
  5. Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 11,743 citations

Related papers

  1. DC-ControlNet: Decoupling Inter- and Intra-Element Conditions in Image Generation with Diffusion ModelsHongji Yang, Wencheng Han, Yucheng Zhou, Jianbing ShenICCV 2025 · 4 citations
  2. FlexiDiT: Your Diffusion Transformer Can Easily Generate High-Quality Samples with Less ComputeSotiris Anagnostidis, Gregor Bachmann, Yeongmin Kim, Jonas Kohler et al.CVPR 2025
  3. Simplifying Control Mechanism in Text-to-Image Diffusion ModelsZhida Feng, Li Chen, Yuenan Sun, Jiaxiang Liu et al.AAAI 2025
  4. Condition-Aware Neural Network for Controlled Image GenerationHan Cai, Muyang Li, Qinsheng Zhang, Ming-Yu Liu et al.CVPR 2024
  5. FreeControl: Training-Free Spatial Control of Any Text-to-Image Diffusion Model with Any ConditionSicheng Mo, Fangzhou Mu, Kuan Heng Lin, Yanli Liu et al.CVPR 2024 · 31 citations
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