Search Results for author: Bin-Bin Gao

Found 23 papers, 11 papers with code

SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning

1 code implementation15 Mar 2023 Jinxiang Lai, Siqian Yang, Wenlong Wu, Tao Wu, Guannan Jiang, Xi Wang, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang

Then we derive two specific attention modules, named SpatialFormer Semantic Attention (SFSA) and SpatialFormer Target Attention (SFTA), to enhance the target object regions while reduce the background distraction.

Few-Shot Learning

HDNet: A Hierarchically Decoupled Network for Crowd Counting

no code implementations12 Dec 2022 Chenliang Gu, Changan Wang, Bin-Bin Gao, Jun Liu, Tianliang Zhang

Recently, density map regression-based methods have dominated in crowd counting owing to their excellent fitting ability on density distribution.

Crowd Counting Density Estimation +1

Global Meets Local: Effective Multi-Label Image Classification via Category-Aware Weak Supervision

no code implementations23 Nov 2022 Jiawei Zhan, Jun Liu, Wei Tang, Guannan Jiang, Xi Wang, Bin-Bin Gao, Tianliang Zhang, Wenlong Wu, Wei zhang, Chengjie Wang, Yuan Xie

This paper builds a unified framework to perform effective noisy-proposal suppression and to interact between global and local features for robust feature learning.

Multi-Label Image Classification

Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective

1 code implementation2 Nov 2022 Jinxiang Lai, Siqian Yang, Guannan Jiang, Xi Wang, Yuxi Li, Zihui Jia, Xiaochen Chen, Jun Liu, Bin-Bin Gao, Wei zhang, Yuan Xie, Chengjie Wang

In this paper, for the first time, we investigate the contributions of different distance metrics, and propose an adaptive fusion scheme, bringing significant improvements in few-shot classification.

Few-Shot Learning

tSF: Transformer-based Semantic Filter for Few-Shot Learning

1 code implementation2 Nov 2022 Jinxiang Lai, Siqian Yang, Wenlong Liu, Yi Zeng, Zhongyi Huang, Wenlong Wu, Jun Liu, Bin-Bin Gao, Chengjie Wang

Few-Shot Learning (FSL) alleviates the data shortage challenge via embedding discriminative target-aware features among plenty seen (base) and few unseen (novel) labeled samples.

Few-Shot Learning object-detection +1

APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation

no code implementations24 Nov 2021 Jiacheng Chen, Bin-Bin Gao, Zongqing Lu, Jing-Hao Xue, Chengjie Wang, Qingmin Liao

In practice, it can adaptively generate multiple class-agnostic prototypes for query images and learn feature alignment in a self-contrastive manner.

Few-Shot Semantic Segmentation Metric Learning +1

A Coarse-to-Fine Instance Segmentation Network with Learning Boundary Representation

no code implementations18 Jun 2021 Feng Luo, Bin-Bin Gao, Jiangpeng Yan, Xiu Li

Experiments also show that our proposed method achieves competitive performance compared to existing boundary-based methods with a lightweight design and a simple pipeline.

Instance Segmentation regression +1

SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes

no code implementations19 Apr 2021 Jiacheng Chen, Bin-Bin Gao, Zongqing Lu, Jing-Hao Xue, Chengjie Wang, Qingmin Liao

To this end, we generate self-contrastive background prototypes directly from the query image, with which we enable the construction of complete sample pairs and thus a complementary and auxiliary segmentation task to achieve the training of a better segmentation model.

Few-Shot Semantic Segmentation Metric Learning +1

Learning to Discover Multi-Class Attentional Regions for Multi-Label Image Recognition

1 code implementation3 Jul 2020 Bin-Bin Gao, Hong-Yu Zhou

To bridge the gap between global and local streams, we propose a multi-class attentional region module which aims to make the number of attentional regions as small as possible and keep the diversity of these regions as high as possible.

Multi-Label Classification Multi-Label Image Classification

Age Estimation Using Expectation of Label Distribution Learning

1 code implementation13 Jul 2018 Bin-Bin Gao, Hong-Yu Zhou, Jianxin Wu, Xin Geng

Age estimation performance has been greatly improved by using convolutional neural network.

Age Estimation Face Recognition +1

A Fast and Robust TSVM for Pattern Classification

1 code implementation15 Nov 2017 Bin-Bin Gao, Jian-Jun Wang

In this paper, we propose a Fast and Robust TSVM~(FR-TSVM) to deal with the above issues.

Classification General Classification +1

Sunrise or Sunset: Selective Comparison Learning for Subtle Attribute Recognition

no code implementations20 Jul 2017 Hong-Yu Zhou, Bin-Bin Gao, Jianxin Wu

The difficulty of image recognition has gradually increased from general category recognition to fine-grained recognition and to the recognition of some subtle attributes such as temperature and geolocation.

Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors

no code implementations ICCV 2017 Hong-Yu Zhou, Bin-Bin Gao, Jianxin Wu

In this paper, we propose Adaptive Feeding (AF) to combine a fast (but less accurate) detector and an accurate (but slow) detector, by adaptively determining whether an image is easy or hard and choosing an appropriate detector for it.

object-detection Object Detection

Deep Label Distribution Learning with Label Ambiguity

2 code implementations6 Nov 2016 Bin-Bin Gao, Chao Xing, Chen-Wei Xie, Jianxin Wu, Xin Geng

However, it is difficult to collect sufficient training images with precise labels in some domains such as apparent age estimation, head pose estimation, multi-label classification and semantic segmentation.

Age Estimation Classification +4

Deep Spatial Pyramid: The Devil is Once Again in the Details

no code implementations21 Apr 2015 Bin-Bin Gao, Xiu-Shen Wei, Jianxin Wu, Weiyao Lin

In this paper we show that by carefully making good choices for various detailed but important factors in a visual recognition framework using deep learning features, one can achieve a simple, efficient, yet highly accurate image classification system.

General Classification Image Classification

Visual Recognition Using Directional Distribution Distance

no code implementations19 Apr 2015 Jianxin Wu, Bin-Bin Gao, Guoqing Liu

In computer vision, an entity such as an image or video is often represented as a set of instance vectors, which can be SIFT, motion, or deep learning feature vectors extracted from different parts of that entity.

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