Search Results for author: Tingbo Hou

Found 16 papers, 1 papers with code

EM Distillation for One-step Diffusion Models

no code implementations27 May 2024 Sirui Xie, Zhisheng Xiao, Diederik P Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao

We propose EM Distillation (EMD), a maximum likelihood-based approach that distills a diffusion model to a one-step generator model with minimal loss of perceptual quality.

3D Congealing: 3D-Aware Image Alignment in the Wild

no code implementations2 Apr 2024 Yunzhi Zhang, Zizhang Li, Amit Raj, Andreas Engelhardt, Yuanzhen Li, Tingbo Hou, Jiajun Wu, Varun Jampani

The framework optimizes for the canonical representation together with the pose for each input image, and a per-image coordinate map that warps 2D pixel coordinates to the 3D canonical frame to account for the shape matching.

Pose Estimation

PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models

no code implementations13 Feb 2024 Fei Deng, Qifei Wang, Wei Wei, Matthias Grundmann, Tingbo Hou

However, in the vision domain, existing RL-based reward finetuning methods are limited by their instability in large-scale training, rendering them incapable of generalizing to complex, unseen prompts.

Denoising Reinforcement Learning (RL)

DreamInpainter: Text-Guided Subject-Driven Image Inpainting with Diffusion Models

no code implementations5 Dec 2023 Shaoan Xie, Yang Zhao, Zhisheng Xiao, Kelvin C. K. Chan, Yandong Li, Yanwu Xu, Kun Zhang, Tingbo Hou

Our extensive experiments demonstrate the superior performance of our method in terms of visual quality, identity preservation, and text control, showcasing its effectiveness in the context of text-guided subject-driven image inpainting.

Image Inpainting

HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models

no code implementations30 Nov 2023 Zhonghao Wang, Wei Wei, Yang Zhao, Zhisheng Xiao, Mark Hasegawa-Johnson, Humphrey Shi, Tingbo Hou

We further extend our method to a novel image editing task: substituting the subject in an image through textual manipulations.

Denoising Image Generation

MobileDiffusion: Subsecond Text-to-Image Generation on Mobile Devices

no code implementations28 Nov 2023 Yang Zhao, Yanwu Xu, Zhisheng Xiao, Tingbo Hou

The deployment of large-scale text-to-image diffusion models on mobile devices is impeded by their substantial model size and slow inference speed.

Computational Efficiency Text-to-Image Generation

UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs

no code implementations14 Nov 2023 Yanwu Xu, Yang Zhao, Zhisheng Xiao, Tingbo Hou

Text-to-image diffusion models have demonstrated remarkable capabilities in transforming textual prompts into coherent images, yet the computational cost of their inference remains a persistent challenge.

Text-to-Image Generation

Towards Authentic Face Restoration with Iterative Diffusion Models and Beyond

no code implementations ICCV 2023 Yang Zhao, Tingbo Hou, Yu-Chuan Su, Xuhui Jia. Yandong Li, Matthias Grundmann

An authentic face restoration system is becoming increasingly demanding in many computer vision applications, e. g., image enhancement, video communication, and taking portrait.

Blind Face Restoration Denoising +2

HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models

2 code implementations13 Jul 2023 Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Wei Wei, Tingbo Hou, Yael Pritch, Neal Wadhwa, Michael Rubinstein, Kfir Aberman

By composing these weights into the diffusion model, coupled with fast finetuning, HyperDreamBooth can generate a person's face in various contexts and styles, with high subject details while also preserving the model's crucial knowledge of diverse styles and semantic modifications.

Diffusion Personalization Tuning Free

CLIP3Dstyler: Language Guided 3D Arbitrary Neural Style Transfer

no code implementations25 May 2023 Ming Gao, Yanwu Xu, Yang Zhao, Tingbo Hou, Chenkai Zhao, Mingming Gong

In this paper, we propose a novel language-guided 3D arbitrary neural style transfer method (CLIP3Dstyler).

Style Transfer

Multiscale Representation for Real-Time Anti-Aliasing Neural Rendering

no code implementations ICCV 2023 Dongting Hu, Zhenkai Zhang, Tingbo Hou, Tongliang Liu, Huan Fu, Mingming Gong

Our approach includes a density Mip-VoG for scene geometry and a feature Mip-VoG with a small MLP for view-dependent color.

Neural Rendering

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