Search Results for author: Dongliang He

Found 44 papers, 24 papers with code

StyleSync: High-Fidelity Generalized and Personalized Lip Sync in Style-based Generator

no code implementations CVPR 2023 Jiazhi Guan, Zhanwang Zhang, Hang Zhou, Tianshu Hu, Kaisiyuan Wang, Dongliang He, Haocheng Feng, Jingtuo Liu, Errui Ding, Ziwei Liu, Jingdong Wang

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability.

Master: Meta Style Transformer for Controllable Zero-Shot and Few-Shot Artistic Style Transfer

no code implementations CVPR 2023 Hao Tang, Songhua Liu, Tianwei Lin, Shaoli Huang, Fu Li, Dongliang He, Xinchao Wang

On the other hand, different from the vanilla version, we adopt a learnable scaling operation on content features before content-style feature interaction, which better preserves the original similarity between a pair of content features while ensuring the stylization quality.

Meta-Learning Style Transfer

DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulation

1 code implementation CVPR 2023 Yueming Lyu, Tianwei Lin, Fu Li, Dongliang He, Jing Dong, Tieniu Tan

Our key idea is to investigate and identify a space, namely delta image and text space that has well-aligned distribution between CLIP visual feature differences of two images and CLIP textual embedding differences of source and target texts.

Image Manipulation

AdaCM: Adaptive ColorMLP for Real-Time Universal Photo-realistic Style Transfer

no code implementations3 Dec 2022 Tianwei Lin, Honglin Lin, Fu Li, Dongliang He, Wenhao Wu, Meiling Wang, Xin Li, Yong liu

Then, in \textbf{AdaCM}, we adopt a CNN encoder to adaptively predict all parameters for the ColorMLP conditioned on each input content and style image pair.

Style Transfer

Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition

1 code implementation22 Nov 2022 Jiaxiang Tang, Kaisiyuan Wang, Hang Zhou, Xiaokang Chen, Dongliang He, Tianshu Hu, Jingtuo Liu, Gang Zeng, Jingdong Wang

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D modeling of talking portraits, the slow training and inference speed severely obstruct their potential usage.

Talking Face Generation

RRSR:Reciprocal Reference-based Image Super-Resolution with Progressive Feature Alignment and Selection

no code implementations8 Nov 2022 Lin Zhang, Xin Li, Dongliang He, Fu Li, Yili Wang, Zhaoxiang Zhang

While previous state-of-the-art RefSR methods mainly focus on improving the efficacy and robustness of reference feature transfer, it is generally overlooked that a well reconstructed SR image should enable better SR reconstruction for its similar LR images when it is referred to as.

feature selection Image Super-Resolution

It Takes Two: Masked Appearance-Motion Modeling for Self-supervised Video Transformer Pre-training

no code implementations11 Oct 2022 Yuxin Song, Min Yang, Wenhao Wu, Dongliang He, Fu Li, Jingdong Wang

In order to guide the encoder to fully excavate spatial-temporal features, two separate decoders are used for two pretext tasks of disentangled appearance and motion prediction.

motion prediction

Effective Invertible Arbitrary Image Rescaling

no code implementations26 Sep 2022 Zhihong Pan, Baopu Li, Dongliang He, Wenhao Wu, Errui Ding

To increase its real world applicability, numerous models have also been proposed to restore SR images with arbitrary scale factors, including asymmetric ones where images are resized to different scales along horizontal and vertical directions.

Image Super-Resolution

CODER: Coupled Diversity-Sensitive Momentum Contrastive Learning for Image-Text Retrieval

no code implementations21 Aug 2022 Haoran Wang, Dongliang He, Wenhao Wu, Boyang xia, Min Yang, Fu Li, Yunlong Yu, Zhong Ji, Errui Ding, Jingdong Wang

We introduce dynamic dictionaries for both modalities to enlarge the scale of image-text pairs, and diversity-sensitiveness is achieved by adaptive negative pair weighting.

Clustering Contrastive Learning +4

Boosting Video-Text Retrieval with Explicit High-Level Semantics

no code implementations8 Aug 2022 Haoran Wang, Di Xu, Dongliang He, Fu Li, Zhong Ji, Jungong Han, Errui Ding

Video-text retrieval (VTR) is an attractive yet challenging task for multi-modal understanding, which aims to search for relevant video (text) given a query (video).

Retrieval Text Retrieval +3

NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition

no code implementations21 Jul 2022 Boyang xia, Wenhao Wu, Haoran Wang, Rui Su, Dongliang He, Haosen Yang, Xiaoran Fan, Wanli Ouyang

On the video level, a temporal attention module is learned under dual video-level supervisions on both the salient and the non-salient representations.

Action Recognition Video Classification +1

Neural Color Operators for Sequential Image Retouching

2 code implementations17 Jul 2022 Yili Wang, Xin Li, Kun Xu, Dongliang He, Qi Zhang, Fu Li, Errui Ding

The neural color operator mimics the behavior of traditional color operators and learns pixelwise color transformation while its strength is controlled by a scalar.

Image Enhancement Image Retouching

DALG: Deep Attentive Local and Global Modeling for Image Retrieval

no code implementations1 Jul 2022 Yuxin Song, Ruolin Zhu, Min Yang, Dongliang He

Deeply learned representations have achieved superior image retrieval performance in a retrieve-then-rerank manner.

Image Retrieval Representation Learning +1

Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence

no code implementations CVPR 2022 Zhihong Pan, Baopu Li, Dongliang He, Mingde Yao, Wenhao Wu, Tianwei Lin, Xin Li, Errui Ding

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 downscaling degradation kernel.

Image Super-Resolution

Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model

1 code implementation CVPR 2022 Zipeng Xu, Tianwei Lin, Hao Tang, Fu Li, Dongliang He, Nicu Sebe, Radu Timofte, Luc van Gool, Errui Ding

We propose a novel framework, i. e., Predict, Prevent, and Evaluate (PPE), for disentangled text-driven image manipulation that requires little manual annotation while being applicable to a wide variety of manipulations.

Image Manipulation Language Modelling

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

2 code implementations ICCV 2021 Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Ruifeng Deng, Xin Li, Errui Ding, Hao Wang

Neural painting refers to the procedure of producing a series of strokes for a given image and non-photo-realistically recreating it using neural networks.

Object Detection Reinforcement Learning (RL) +1

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

3 code implementations ICCV 2021 Songhua Liu, Tianwei Lin, Dongliang He, Fu Li, Meiling Wang, Xin Li, Zhengxing Sun, Qian Li, Errui Ding

Finally, the content feature is normalized so that they demonstrate the same local feature statistics as the calculated per-point weighted style feature statistics.

Style Transfer Video Style Transfer

Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings

3 code implementations15 Jun 2021 Hengyuan Zhao, Wenhao Wu, Yihao Liu, Dongliang He

In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed.

Colorization Image Colorization +1

Image Inpainting by End-to-End Cascaded Refinement with Mask Awareness

1 code implementation28 Apr 2021 Manyu Zhu, Dongliang He, Xin Li, Chao Li, Fu Li, Xiao Liu, Errui Ding, Zhaoxiang Zhang

Inpainting arbitrary missing regions is challenging because learning valid features for various masked regions is nontrivial.

Image Inpainting valid

Learning Semantic Person Image Generation by Region-Adaptive Normalization

1 code implementation CVPR 2021 Zhengyao Lv, Xiaoming Li, Xin Li, Fu Li, Tianwei Lin, Dongliang He, WangMeng Zuo

In the first stage, we predict the target semantic parsing maps to eliminate the difficulties of pose transfer and further benefit the latter translation of per-region appearance style.

Pose Transfer Semantic Parsing +1

Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer

2 code implementations CVPR 2021 Tianwei Lin, Zhuoqi Ma, Fu Li, Dongliang He, Xin Li, Errui Ding, Nannan Wang, Jie Li, Xinbo Gao

Inspired by the common painting process of drawing a draft and revising the details, we introduce a novel feed-forward method named Laplacian Pyramid Network (LapStyle).

Style Transfer

MVFNet: Multi-View Fusion Network for Efficient Video Recognition

3 code implementations13 Dec 2020 Wenhao Wu, Dongliang He, Tianwei Lin, Fu Li, Chuang Gan, Errui Ding

Existing state-of-the-art methods have achieved excellent accuracy regardless of the complexity meanwhile efficient spatiotemporal modeling solutions are slightly inferior in performance.

Action Classification Action Recognition +2

RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning

1 code implementation27 Oct 2020 Peihao Chen, Deng Huang, Dongliang He, Xiang Long, Runhao Zeng, Shilei Wen, Mingkui Tan, Chuang Gan

We study unsupervised video representation learning that seeks to learn both motion and appearance features from unlabeled video only, which can be reused for downstream tasks such as action recognition.

Representation Learning Retrieval +2

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

2 code implementations15 Oct 2020 Pengcheng Yuan, Shufei Lin, Cheng Cui, Yuning Du, Ruoyu Guo, Dongliang He, Errui Ding, Shumin Han

Moreover, Hierarchical-Split block is very flexible and efficient, which provides a large space of potential network architectures for different applications.

Image Classification Image Segmentation +5

Dynamic Inference: A New Approach Toward Efficient Video Action Recognition

no code implementations9 Feb 2020 Wenhao Wu, Dongliang He, Xiao Tan, Shifeng Chen, Yi Yang, Shilei Wen

In a nutshell, we treat input frames and network depth of the computational graph as a 2-dimensional grid, and several checkpoints are placed on this grid in advance with a prediction module.

Action Recognition In Videos Temporal Action Localization

Multi-Label Classification with Label Graph Superimposing

2 code implementations21 Nov 2019 Ya Wang, Dongliang He, Fu Li, Xiang Long, Zhichao Zhou, Jinwen Ma, Shilei Wen

In this paper, we propose a label graph superimposing framework to improve the conventional GCN+CNN framework developed for multi-label recognition in the following two aspects.

Attribute Classification +3

TruNet: Short Videos Generation from Long Videos via Story-Preserving Truncation

no code implementations14 Oct 2019 Fan Yang, Xiao Liu, Dongliang He, Chuang Gan, Jian Wang, Chao Li, Fu Li, Shilei Wen

In this work, we introduce a new problem, named as {\em story-preserving long video truncation}, that requires an algorithm to automatically truncate a long-duration video into multiple short and attractive sub-videos with each one containing an unbroken story.

Highlight Detection Video Summarization

Deep Concept-wise Temporal Convolutional Networks for Action Localization

2 code implementations26 Aug 2019 Xin Li, Tianwei Lin, Xiao Liu, Chuang Gan, WangMeng Zuo, Chao Li, Xiang Long, Dongliang He, Fu Li, Shilei Wen

In this paper, we empirically find that stacking more conventional temporal convolution layers actually deteriorates action classification performance, possibly ascribing to that all channels of 1D feature map, which generally are highly abstract and can be regarded as latent concepts, are excessively recombined in temporal convolution.

Action Classification Action Localization

Adapting Image Super-Resolution State-of-the-arts and Learning Multi-model Ensemble for Video Super-Resolution

no code implementations7 May 2019 Chao Li, Dongliang He, Xiao Liu, Yukang Ding, Shilei Wen

Recently, image super-resolution has been widely studied and achieved significant progress by leveraging the power of deep convolutional neural networks.

Image Super-Resolution Video Super-Resolution

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

1 code implementation21 Jan 2019 Dongliang He, Xiang Zhao, Jizhou Huang, Fu Li, Xiao Liu, Shilei Wen

The task of video grounding, which temporally localizes a natural language description in a video, plays an important role in understanding videos.

Decision Making Multi-Task Learning +3

StNet: Local and Global Spatial-Temporal Modeling for Action Recognition

8 code implementations5 Nov 2018 Dongliang He, Zhichao Zhou, Chuang Gan, Fu Li, Xiao Liu, Yandong Li, Li-Min Wang, Shilei Wen

In this paper, in contrast to the existing CNN+RNN or pure 3D convolution based approaches, we explore a novel spatial temporal network (StNet) architecture for both local and global spatial-temporal modeling in videos.

Action Recognition Temporal Action Localization

Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition

no code implementations27 Jun 2018 Dongliang He, Fu Li, Qijie Zhao, Xiang Long, Yi Fu, Shilei Wen

In this challenge, we propose spatial-temporal network (StNet) for better joint spatial-temporal modelling and comprehensively video understanding.

Action Recognition Temporal Action Localization +1

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