Search Results for author: Fangyun Wei

Found 16 papers, 11 papers with code

Towards Tokenized Human Dynamics Representation

1 code implementation22 Nov 2021 Kenneth Li, Xiao Sun, Zhirong Wu, Fangyun Wei, Stephen Lin

For human action understanding, a popular research direction is to analyze short video clips with unambiguous semantic content, such as jumping and drinking.

Action Segmentation Action Understanding +4

Bootstrap Your Object Detector via Mixed Training

1 code implementation NeurIPS 2021 Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Stephen Lin, Han Hu, Xiang Bai

We introduce MixTraining, a new training paradigm for object detection that can improve the performance of existing detectors for free.

Data Augmentation Object Detection

Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning

1 code implementation NeurIPS 2021 Hanzhe Hu, Fangyun Wei, Han Hu, Qiwei Ye, Jinshi Cui, LiWei Wang

The confidence bank is leveraged as an indicator to tilt training towards under-performing categories, instantiated in three strategies: 1) adaptive Copy-Paste and CutMix data augmentation approaches which give more chance for under-performing categories to be copied or cut; 2) an adaptive data sampling approach to encourage pixels from under-performing category to be sampled; 3) a simple yet effective re-weighting method to alleviate the training noise raised by pseudo-labeling.

Data Augmentation Semi-Supervised Semantic Segmentation

Self-supervised Discovery of Human Actons from Long Kinematic Videos

no code implementations29 Sep 2021 Kenneth Li, Xiao Sun, Zhirong Wu, Fangyun Wei, Stephen Lin

However, methods for understanding short semantic actions cannot be directly translated to long kinematic sequences such as dancing, where it becomes challenging even to semantically label the human movements.

Action Understanding Tokenization

ADNet: Leveraging Error-Bias Towards Normal Direction in Face Alignment

no code implementations ICCV 2021 Yangyu Huang, Hao Yang, Chong Li, Jongyoo Kim, Fangyun Wei

On the other hand, AAM is an attention module which can get anisotropic attention mask focusing on the region of point and its local edge connected by adjacent points, it has a stronger response in tangent than in normal, which means relaxed constraints in the tangent.

Face Alignment

Dual Path Learning for Domain Adaptation of Semantic Segmentation

1 code implementation ICCV 2021 Yiting Cheng, Fangyun Wei, Jianmin Bao, Dong Chen, Fang Wen, Wenqiang Zhang

In this paper, based on the observation that domain adaptation frameworks performed in the source and target domain are almost complementary in terms of image translation and SSL, we propose a novel dual path learning (DPL) framework to alleviate visual inconsistency.

Domain Adaptation Self-Supervised Learning +3

Aligning Pretraining for Detection via Object-Level Contrastive Learning

1 code implementation NeurIPS 2021 Fangyun Wei, Yue Gao, Zhirong Wu, Han Hu, Stephen Lin

Image-level contrastive representation learning has proven to be highly effective as a generic model for transfer learning.

Contrastive Learning Object Detection +3

High-Fidelity and Arbitrary Face Editing

no code implementations CVPR 2021 Yue Gao, Fangyun Wei, Jianmin Bao, Shuyang Gu, Dong Chen, Fang Wen, Zhouhui Lian

However, we observe that the generator tends to find a tricky way to hide information from the original image to satisfy the constraint of cycle consistency, making it impossible to maintain the rich details (e. g., wrinkles and moles) of non-editing areas.

Global Context Networks

3 code implementations24 Dec 2020 Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu

The Non-Local Network (NLNet) presents a pioneering approach for capturing long-range dependencies within an image, via aggregating query-specific global context to each query position.

Instance Segmentation

Restoring Negative Information in Few-Shot Object Detection

1 code implementation NeurIPS 2020 Yukuan Yang, Fangyun Wei, Miaojing Shi, Guoqi Li

In this paper, we restore the negative information in few-shot object detection by introducing a new negative- and positive-representative based metric learning framework and a new inference scheme with negative and positive representatives.

Few-Shot Learning Few-Shot Object Detection +2

Point-Set Anchors for Object Detection, Instance Segmentation and Pose Estimation

1 code implementation ECCV 2020 Fangyun Wei, Xiao Sun, Hongyang Li, Jingdong Wang, Stephen Lin

A recent approach for object detection and human pose estimation is to regress bounding boxes or human keypoints from a central point on the object or person.

Instance Segmentation Object Detection +2

Design and Interpretation of Universal Adversarial Patches in Face Detection

no code implementations ECCV 2020 Xiao Yang, Fangyun Wei, Hongyang Zhang, Jun Zhu

We consider universal adversarial patches for faces -- small visual elements whose addition to a face image reliably destroys the performance of face detectors.

Face Detection

GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

9 code implementations25 Apr 2019 Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu

In this paper, we take advantage of this finding to create a simplified network based on a query-independent formulation, which maintains the accuracy of NLNet but with significantly less computation.

Instance Segmentation Object Detection +1

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