20 citations · 57 across the 15 of their papers we have counts for
15 papers
GBSD: Generative Bokeh with Stage Diffusion
Jieren Deng, Xin Zhou, Hao Tian +2
The bokeh effect is an artistic technique that blurs out-of-focus areas in a photograph and has gained interest due to recent developments in text-to-image synthesis and the ubiqui…
Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis
Yansong Gao, Zhihong Pan, Xin Zhou +2
Denoising diffusion probabilistic models (DDPMs) are a class of powerful generative models. The past few years have witnessed the great success of DDPMs in generating high-fidelity…
Raising The Limit Of Image Rescaling Using Auxiliary Encoding
Chenzhong Yin, Zhihong Pan, Xin Zhou +2
Normalizing flow models using invertible neural networks (INN) have been widely investigated for successful generative image super-resolution (SR) by learning the transformation be…
Extreme Generative Image Compression by Learning Text Embedding from Diffusion Models
Zhihong Pan, Xin Zhou, Hao Tian
Transferring large amount of high resolution images over limited bandwidth is an important but very challenging task. Compressing images using extremely low bitrates (<0.1 bpp) has…
Arbitrary Style Guidance for Enhanced Diffusion-Based Text-to-Image Generation
Zhihong Pan, Xin Zhou, Hao Tian
Diffusion-based text-to-image generation models like GLIDE and DALLE-2 have gained wide success recently for their superior performance in turning complex text inputs into images o…
Diffusion Motion: Generate Text-Guided 3D Human Motion by Diffusion Model
Zhiyuan Ren, Zhihong Pan, Xin Zhou +1
We propose a simple and novel method for generating 3D human motion from complex natural language sentences, which describe different velocity, direction and composition of all kin…
Effective Invertible Arbitrary Image Rescaling
Zhihong Pan, Baopu Li, Dongliang He +2
Great successes have been achieved using deep learning techniques for image super-resolution (SR) with fixed scales. To increase its real world applicability, numerous models have…
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network
Min Zhang, Zhihong Pan, Xin Zhou +1
Normalizing flow models have been used successfully for generative image super-resolution (SR) by approximating complex distribution of natural images to simple tractable distribut…
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence
Zhihong Pan, Baopu Li, Dongliang He +5
Deep learning based single image super-resolution models have been widely studied and superb results are achieved in upscaling low-resolution images with fixed scale factor and dow…
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov, Radu Timofte, Zhilu Zhang +36
This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. The participating teams were solving a real-world RAW-to…
AutoPruning for Deep Neural Network with Dynamic Channel Masking
Baopu Li, Yanwen Fan, Zhihong Pan +1
Modern deep neural network models are large and computationally intensive. One typical solution to this issue is model pruning. However, most current pruning algorithms depend on h…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
Real Image Super Resolution Via Heterogeneous Model Ensemble using GP-NAS
Zhihong Pan, Baopu Li, Teng Xi +5
With advancement in deep neural network (DNN), recent state-of-the-art (SOTA) image superresolution (SR) methods have achieved impressive performance using deep residual network wi…
UDC 2020 Challenge on Image Restoration of Under-Display Camera: Methods and Results
Yuqian Zhou, Michael Kwan, Kyle Tolentino +42
This paper is the report of the first Under-Display Camera (UDC) image restoration challenge in conjunction with the RLQ workshop at ECCV 2020. The challenge is based on a newly-co…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…