Search Results for author: Fei Zhang

Found 12 papers, 4 papers with code

Audio-Visual Segmentation via Unlabeled Frame Exploitation

no code implementations17 Mar 2024 Jinxiang Liu, Yikun Liu, Fei Zhang, Chen Ju, Ya zhang, Yanfeng Wang

NFs, temporally adjacent to the labeled frame, often contain rich motion information that assists in the accurate localization of sounding objects.

valid

Exploiting Counter-Examples for Active Learning with Partial labels

no code implementations14 Jul 2023 Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han

In this setting, an oracle annotates the query samples with partial labels, relaxing the oracle from the demanding accurate labeling process.

Active Learning

Prediction of Post-Operative Renal and Pulmonary Complications Using Transformers

no code implementations1 Jun 2023 Reza Shirkavand, Fei Zhang, Heng Huang

This work highlights the potential of deep learning techniques, specifically transformer-based models, in revolutionizing the healthcare industry's approach to postoperative care.

Management

Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection

1 code implementation ICCV 2023 Boyang Li, Yingqian Wang, Longguang Wang, Fei Zhang, Ting Liu, Zaiping Lin, Wei An, Yulan Guo

The core idea of this work is to recover the per-pixel mask of each target from the given single point label by using clustering approaches, which looks simple but is indeed challenging since targets are always insalient and accompanied with background clutters.

Clustering

DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery

no code implementations17 Mar 2023 Chaofan Ma, Yuhuan Yang, Chen Ju, Fei Zhang, Jinxiang Liu, Yu Wang, Ya zhang, Yanfeng Wang

However, the challenges exist as there is one structural difference between generative and discriminative models, which limits the direct use.

Object Object Discovery +1

Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation

no code implementations4 Mar 2023 Jiren Mai, Fei Zhang, Junjie Ye, Marcus Kalander, Xian Zhang, Wankou Yang, Tongliang Liu, Bo Han

Motivated by this simple but effective learning pattern, we propose a General-Specific Learning Mechanism (GSLM) to explicitly drive a coarse-grained CAM to a fine-grained pseudo mask.

General Knowledge Hippocampus +2

Exploiting Class Activation Value for Partial-Label Learning

3 code implementations ICLR 2022 Fei Zhang, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Tao Qin, Masashi Sugiyama

As the first contribution, we empirically show that the class activation map (CAM), a simple technique for discriminating the learning patterns of each class in images, is surprisingly better at making accurate predictions than the model itself on selecting the true label from candidate labels.

Multi-class Classification Partial Label Learning

Complementary Patch for Weakly Supervised Semantic Segmentation

1 code implementation ICCV 2021 Fei Zhang, Chaochen Gu, Chenyue Zhang, Yuchao Dai

Therefore, a CAM with more information related to object seeds can be obtained by narrowing down the gap between the sum of CAMs generated by the CP Pair and the original CAM.

Segmentation Weakly supervised Semantic Segmentation +1

An Improved Algorithm of Robot Path Planning in Complex Environment Based on Double DQN

no code implementations23 Jul 2021 Fei Zhang, Chaochen Gu, Feng Yang

Deep Q Network (DQN) has several limitations when applied in planning a path in environment with a number of dilemmas according to our experiment.

Adversarial Feature Selection against Evasion Attacks

1 code implementation25 May 2020 Fei Zhang, Patrick P. K. Chan, Battista Biggio, Daniel S. Yeung, Fabio Roli

Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed.

feature selection Malware Detection

Relative distance features for gait recognition with Kinect

no code implementations18 May 2016 Ke Yang, Yong Dou, Shaohe Lv, Fei Zhang, Qi Lv

This study focuses on human recognition with gait feature obtained by Kinect and shows that gait feature can effectively distinguish from different human beings through a novel representation -- relative distance-based gait features.

Gait Recognition

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