DiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

no code implementations • 26 Mar 2024 • Qilin Wang, Jiangning Zhang, Chengming Xu, Weijian Cao, Ying Tai, Yue Han, Yanhao Ge, Hong Gu, Chengjie Wang, Yanwei Fu

Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in photograph.

Attribute Semantic Composition

Faster OreFSDet : A Lightweight and Effective Few-shot Object Detector for Ore Images

1 code implementation • 2 May 2023 • Yang Zhang, Le Cheng, Yuting Peng, Chengming Xu, Yanwei Fu, Bo Wu, Guodong Sun

For the ore particle size detection, obtaining a sizable amount of high-quality ore labeled data is time-consuming and expensive.

Object object-detection +1

Exploring Efficient Few-shot Adaptation for Vision Transformers

1 code implementation • 6 Jan 2023 • Chengming Xu, Siqian Yang, Yabiao Wang, Zhanxiong Wang, Yanwei Fu, xiangyang xue

Essentially, despite ViTs have been shown to enjoy comparable or even better performance on other vision tasks, it is still very nontrivial to efficiently finetune the ViTs in real-world FSL scenarios.

Few-Shot Learning

Split-PU: Hardness-aware Training Strategy for Positive-Unlabeled Learning

1 code implementation • 30 Nov 2022 • Chengming Xu, Chen Liu, Siqian Yang, Yabiao Wang, Shijie Zhang, Lijie Jia, Yanwei Fu

Since only part of the most confident positive samples are available and evidence is not enough to categorize the rest samples, many of these unlabeled data may also be the positive samples.

Binary Classification

PatchMix Augmentation to Identify Causal Features in Few-shot Learning

no code implementations • 29 Nov 2022 • Chengming Xu, Chen Liu, Xinwei Sun, Siqian Yang, Yabiao Wang, Chengjie Wang, Yanwei Fu

We theoretically show that such an augmentation mechanism, different from existing ones, is able to identify the causal features.

Data Augmentation Few-Shot Learning +1

The Image Local Autoregressive Transformer

1 code implementation • NeurIPS 2021 • Chenjie Cao, Yuxin Hong, Xiang Li, Chengrong Wang, Chengming Xu, xiangyang xue, Yanwei Fu

To address these limitations, we propose a novel model -- image Local Autoregressive Transformer (iLAT), to better facilitate the locally guided image synthesis.

Image Generation

Learning Dynamic Alignment via Meta-filter for Few-shot Learning

1 code implementation • CVPR 2021 • Chengming Xu, Chen Liu, Li Zhang, Chengjie Wang, Jilin Li, Feiyue Huang, xiangyang xue, Yanwei Fu

Our insight is that these methods would lead to poor adaptation with redundant matching, and leveraging channel-wise adjustment is the key to well adapting the learned knowledge to new classes.

Few-Shot Learning Position

Learning Salient Boundary Feature for Anchor-free Temporal Action Localization

1 code implementation • CVPR 2021 • Chuming Lin, Chengming Xu, Donghao Luo, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Yanwei Fu

Temporal action localization is an important yet challenging task in video understanding.

Temporal Action Localization Temporal Localization +1

Instance Credibility Inference for Few-Shot Learning

1 code implementation • CVPR 2020 • Yikai Wang, Chengming Xu, Chen Liu, Li Zhang, Yanwei Fu

To measure the credibility of each pseudo-labeled instance, we then propose to solve another linear regression hypothesis by increasing the sparsity of the incidental parameters and rank the pseudo-labeled instances with their sparsity degree.

Data Augmentation Few-Shot Image Classification +2

Learning to score the figure skating sports videos

1 code implementation • 8 Feb 2018 • Chengming Xu, Yanwei Fu, Bing Zhang, Zitian Chen, Yu-Gang Jiang, xiangyang xue

This paper targets at learning to score the figure skating sports videos.