Search Results for author: Yunfan Liu

Found 22 papers, 9 papers with code

A Simple yet Effective DDG Predictor is An Unsupervised Antibody Optimizer and Explainer

1 code implementation10 Feb 2025 Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Guojiang Zhao, Zhifeng Gao, Stan Z. Li

For the target antibody, we propose a novel Mutation Explainer to learn mutation preferences, which accounts for the marginal benefit of each mutation per residue.

Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization

no code implementations14 Dec 2024 Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li

Antibodies are Y-shaped proteins that protect the host by binding to specific antigens, and their binding is mainly determined by the Complementary Determining Regions (CDRs) in the antibody.

Relation Specificity

CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis

no code implementations11 Dec 2024 Mu Zhang, Yunfan Liu, Yue Liu, Hongtian Yu, Qixiang Ye

Accurately depicting real-world landscapes in remote sensing (RS) images requires precise alignment between objects and their environment.

Image Generation

Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition

1 code implementation28 Nov 2024 Hongda Liu, Yunfan Liu, Min Ren, Hao Wang, Yunlong Wang, Zhenan Sun

In skeleton-based action recognition, a key challenge is distinguishing between actions with similar trajectories of joints due to the lack of image-level details in skeletal representations.

Action Recognition Skeleton Based Action Recognition

Vision Calorimeter: Migrating Visual Object Detector to High-energy Particle Images

1 code implementation20 Aug 2024 Hongtian Yu, Yangu Li, Yunfan Liu, Yunxuan Song, Xiaorui Lyu, Qixiang Ye

To address this issue, we propose Vision Calorimeter (ViC), a data-driven framework which migrates visual object detection techniques to high-energy particle images.

Deep Learning object-detection +2

Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation

1 code implementation20 Jul 2024 Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Stan Z. Li

To bridge the gaps between powerful Graph Neural Networks (GNNs) and lightweight Multi-Layer Perceptron (MLPs), GNN-to-MLP Knowledge Distillation (KD) proposes to distill knowledge from a well-trained teacher GNN into a student MLP.

Knowledge Distillation

Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences

no code implementations12 Jun 2024 Zicheng Liu, Siyuan Li, Li Wang, Zedong Wang, Yunfan Liu, Stan Z. Li

To mitigate the computational complexity in the self-attention mechanism on long sequences, linear attention utilizes computation tricks to achieve linear complexity, while state space models (SSMs) popularize a favorable practice of using non-data-dependent memory pattern, i. e., emphasize the near and neglect the distant, to processing sequences.

Language Modeling Long-range modeling +1

vHeat: Building Vision Models upon Heat Conduction

1 code implementation26 May 2024 Zhaozhi Wang, Yue Liu, Yunfan Liu, Hongtian Yu, YaoWei Wang, Qixiang Ye, Yunjie Tian

A fundamental problem in learning robust and expressive visual representations lies in efficiently estimating the spatial relationships of visual semantics throughout the entire image.

Computational Efficiency

VMamba: Visual State Space Model

12 code implementations18 Jan 2024 Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, YaoWei Wang, Qixiang Ye, Jianbin Jiao, Yunfan Liu

At the core of VMamba is a stack of Visual State-Space (VSS) blocks with the 2D Selective Scan (SS2D) module.

Computational Efficiency Language Modeling +4

Spatial Transform Decoupling for Oriented Object Detection

1 code implementation21 Aug 2023 Hongtian Yu, Yunjie Tian, Qixiang Ye, Yunfan Liu

Vision Transformers (ViTs) have achieved remarkable success in computer vision tasks.

Ranked #2 on Object Detection In Aerial Images on HRSC2016 (using extra training data)

Object object-detection +2

3D-Aware Adversarial Makeup Generation for Facial Privacy Protection

no code implementations26 Jun 2023 Yueming Lyu, Yue Jiang, Ziwen He, Bo Peng, Yunfan Liu, Jing Dong

The privacy and security of face data on social media are facing unprecedented challenges as it is vulnerable to unauthorized access and identification.

Face Recognition Face Verification

Semantic-aware One-shot Face Re-enactment with Dense Correspondence Estimation

no code implementations23 Nov 2022 Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan

One-shot face re-enactment is a challenging task due to the identity mismatch between source and driving faces.

Disentanglement Generative Adversarial Network

GAN-based Facial Attribute Manipulation

no code implementations23 Oct 2022 Yunfan Liu, Qi Li, Qiyao Deng, Zhenan Sun, Ming-Hsuan Yang

Facial Attribute Manipulation (FAM) aims to aesthetically modify a given face image to render desired attributes, which has received significant attention due to its broad practical applications ranging from digital entertainment to biometric forensics.

Attribute Survey

Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?

no code implementations19 Nov 2020 Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan

Generative Adversarial Networks (GANs) with style-based generators (e. g. StyleGAN) successfully enable semantic control over image synthesis, and recent studies have also revealed that interpretable image translations could be obtained by modifying the latent code.

Attribute Disentanglement +2

A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging

no code implementations15 Nov 2019 Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan

Face aging, which aims at aesthetically rendering a given face to predict its future appearance, has received significant research attention in recent years.

Attribute Generative Adversarial Network

Age Progression and Regression with Spatial Attention Modules

no code implementations6 Mar 2019 Qi Li, Yunfan Liu, Zhenan Sun

Age progression and regression refers to aesthetically render-ing a given face image to present effects of face aging and rejuvenation, respectively.

regression Translation

Joint Iris Segmentation and Localization Using Deep Multi-task Learning Framework

1 code implementation31 Jan 2019 Caiyong Wang, Yuhao Zhu, Yunfan Liu, Ran He, Zhenan Sun

In this paper, we propose a deep multi-task learning framework, named as IrisParseNet, to exploit the inherent correlations between pupil, iris and sclera to boost up the performance of iris segmentation and localization in a unified model.

Decoder Iris Segmentation +2

Attribute-aware Face Aging with Wavelet-based Generative Adversarial Networks

no code implementations CVPR 2019 Yunfan Liu, Qi Li, Zhenan Sun

Since it is difficult to collect face images of the same subject over a long range of age span, most existing face aging methods resort to unpaired datasets to learn age mappings.

Attribute

Learning to Detect Human-Object Interactions

no code implementations17 Feb 2017 Yu-Wei Chao, Yunfan Liu, Xieyang Liu, Huayi Zeng, Jia Deng

We study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them.

General Classification Human-Object Interaction Detection +1

Combining Data-driven and Model-driven Methods for Robust Facial Landmark Detection

1 code implementation30 Nov 2016 Hongwen Zhang, Qi Li, Zhenan Sun, Yunfan Liu

This Estimation-Correction-Tuning process perfectly combines the advantages of the global robustness of data-driven method (FCN), outlier correction capability of model-driven method (PDM) and non-parametric optimization of RLMS.

Facial Landmark Detection

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