Search Results for author: Yingchen Yu

Found 23 papers, 9 papers with code

EMLight: Lighting Estimation via Spherical Distribution Approximation

no code implementations21 Dec 2020 Fangneng Zhan, Changgong Zhang, Yingchen Yu, Yuan Chang, Shijian Lu, Feiying Ma, Xuansong Xie

Motivated by the Earth Mover distance, we design a novel spherical mover's loss that guides to regress light distribution parameters accurately by taking advantage of the subtleties of spherical distribution.

Lighting Estimation regression

GMLight: Lighting Estimation via Geometric Distribution Approximation

1 code implementation20 Feb 2021 Fangneng Zhan, Yingchen Yu, Changgong Zhang, Rongliang Wu, WenBo Hu, Shijian Lu, Feiying Ma, Xuansong Xie, Ling Shao

This paper presents Geometric Mover's Light (GMLight), a lighting estimation framework that employs a regression network and a generative projector for effective illumination estimation.

Lighting Estimation regression

Diverse Image Inpainting with Bidirectional and Autoregressive Transformers

no code implementations26 Apr 2021 Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jianxiong Pan, Kaiwen Cui, Shijian Lu, Feiying Ma, Xuansong Xie, Chunyan Miao

With image-level attention, transformers enable to model long-range dependencies and generate diverse contents with autoregressive modeling of pixel-sequence distributions.

Image Inpainting Language Modelling

Blind Image Super-Resolution via Contrastive Representation Learning

no code implementations1 Jul 2021 Jiahui Zhang, Shijian Lu, Fangneng Zhan, Yingchen Yu

Extensive experiments on synthetic datasets and real images show that the proposed CRL-SR can handle multi-modal and spatially variant degradation effectively under blind settings and it also outperforms state-of-the-art SR methods qualitatively and quantitatively.

Contrastive Learning Image Super-Resolution +1

Bi-level Feature Alignment for Versatile Image Translation and Manipulation

2 code implementations7 Jul 2021 Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Aoran Xiao, Shijian Lu, Chunyan Miao

This paper presents a versatile image translation and manipulation framework that achieves accurate semantic and style guidance in image generation by explicitly building a correspondence.

Image Generation Translation

WaveFill: A Wavelet-based Generation Network for Image Inpainting

1 code implementation ICCV 2021 Yingchen Yu, Fangneng Zhan, Shijian Lu, Jianxiong Pan, Feiying Ma, Xuansong Xie, Chunyan Miao

This paper presents WaveFill, a wavelet-based inpainting network that decomposes images into multiple frequency bands and fills the missing regions in each frequency band separately and explicitly.

Image Inpainting

Multimodal Image Synthesis and Editing: The Generative AI Era

2 code implementations27 Dec 2021 Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Lingjie Liu, Adam Kortylewski, Christian Theobalt, Eric Xing

With superb power in modeling the interaction among multimodal information, multimodal image synthesis and editing has become a hot research topic in recent years.

Image Generation

Accelerating DETR Convergence via Semantic-Aligned Matching

1 code implementation CVPR 2022 Gongjie Zhang, Zhipeng Luo, Yingchen Yu, Kaiwen Cui, Shijian Lu

First, it projects object queries into the same embedding space as encoded image features, where the matching can be accomplished efficiently with aligned semantics.

Object object-detection +1

Modulated Contrast for Versatile Image Synthesis

1 code implementation CVPR 2022 Fangneng Zhan, Jiahui Zhang, Yingchen Yu, Rongliang Wu, Shijian Lu

Perceiving the similarity between images has been a long-standing and fundamental problem underlying various visual generation tasks.

Contrastive Learning Image Generation

Marginal Contrastive Correspondence for Guided Image Generation

no code implementations CVPR 2022 Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Shijian Lu, Changgong Zhang

We design a Marginal Contrastive Learning Network (MCL-Net) that explores contrastive learning to learn domain-invariant features for realistic exemplar-based image translation.

Contrastive Learning Image Generation +2

Towards Counterfactual Image Manipulation via CLIP

1 code implementation6 Jul 2022 Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jiahui Zhang, Shijian Lu, Miaomiao Cui, Xuansong Xie, Xian-Sheng Hua, Chunyan Miao

In addition, we design a simple yet effective scheme that explicitly maps CLIP embeddings (of target text) to the latent space and fuses them with latent codes for effective latent code optimization and accurate editing.

counterfactual Image Manipulation

VMRF: View Matching Neural Radiance Fields

no code implementations6 Jul 2022 Jiahui Zhang, Fangneng Zhan, Rongliang Wu, Yingchen Yu, Wenqing Zhang, Bai Song, Xiaoqin Zhang, Shijian Lu

With the feature transport plan as the guidance, a novel pose calibration technique is designed which rectifies the initially randomized camera poses by predicting relative pose transformations between the pair of rendered and real images.

Novel View Synthesis

Auto-regressive Image Synthesis with Integrated Quantization

no code implementations21 Jul 2022 Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Changgong Zhang, Shijian Lu

Extensive experiments over multiple conditional image generation tasks show that our method achieves superior diverse image generation performance qualitatively and quantitatively as compared with the state-of-the-art.

Conditional Image Generation Inductive Bias +1

Latent Multi-Relation Reasoning for GAN-Prior based Image Super-Resolution

no code implementations4 Aug 2022 Jiahui Zhang, Fangneng Zhan, Yingchen Yu, Rongliang Wu, Xiaoqin Zhang, Shijian Lu

In addition, stochastic noises fed to the generator are employed for unconditional detail generation, which tends to produce unfaithful details that compromise the fidelity of the generated SR image.

Attribute Code Generation +3

StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields

1 code implementation CVPR 2023 Kunhao Liu, Fangneng Zhan, YiWen Chen, Jiahui Zhang, Yingchen Yu, Abdulmotaleb El Saddik, Shijian Lu, Eric Xing

In addition, it transforms the grid features according to the reference style which directly leads to high-quality zero-shot style transfer.

Style Transfer

KD-DLGAN: Data Limited Image Generation via Knowledge Distillation

no code implementations CVPR 2023 Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao, Shijian Lu1, Eric Xing

The first is aggregated generative KD that mitigates the discriminator overfitting by challenging the discriminator with harder learning tasks and distilling more generalizable knowledge from the pre-trained models.

Image Generation Knowledge Distillation

Audio-Driven Talking Face Generation with Diverse yet Realistic Facial Animations

no code implementations18 Apr 2023 Rongliang Wu, Yingchen Yu, Fangneng Zhan, Jiahui Zhang, Xiaoqin Zhang, Shijian Lu

To accommodate fair variation of plausible facial animations for the same audio, we design a transformer-based probabilistic mapping network that can model the variational facial animation distribution conditioned upon the input audio and autoregressively convert the audio signals into a facial animation sequence.

Talking Face Generation

POCE: Pose-Controllable Expression Editing

no code implementations18 Apr 2023 Rongliang Wu, Yingchen Yu, Fangneng Zhan, Jiahui Zhang, Shengcai Liao, Shijian Lu

POCE achieves the more accessible and realistic pose-controllable expression editing by mapping face images into UV space, where facial expressions and head poses can be disentangled and edited separately.

Weakly Supervised 3D Open-vocabulary Segmentation

1 code implementation NeurIPS 2023 Kunhao Liu, Fangneng Zhan, Jiahui Zhang, Muyu Xu, Yingchen Yu, Abdulmotaleb El Saddik, Christian Theobalt, Eric Xing, Shijian Lu

Open-vocabulary segmentation of 3D scenes is a fundamental function of human perception and thus a crucial objective in computer vision research.

Segmentation

Pose-Free Neural Radiance Fields via Implicit Pose Regularization

no code implementations ICCV 2023 Jiahui Zhang, Fangneng Zhan, Yingchen Yu, Kunhao Liu, Rongliang Wu, Xiaoqin Zhang, Ling Shao, Shijian Lu

However, as the pose estimator is trained with only rendered images, the pose estimation is usually biased or inaccurate for real images due to the domain gap between real images and rendered images, leading to poor robustness for the pose estimation of real images and further local minima in joint optimization.

Novel View Synthesis Pose Estimation

Debiasing Text-to-Image Diffusion Models

no code implementations22 Feb 2024 Ruifei He, Chuhui Xue, Haoru Tan, Wenqing Zhang, Yingchen Yu, Song Bai, Xiaojuan Qi

Despite its simplicity, we show that IDA shows efficiency and fast convergence in resolving the social bias in TTI diffusion models.

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