Search Results for author: Jun Yue

Found 7 papers, 2 papers with code

Large-Scale Few-Shot Learning via Multi-Modal Knowledge Discovery

no code implementations ECCV 2020 Shuo Wang, Jun Yue, Jianzhuang Liu, Qi Tian, Meng Wang

It is a challenging problem since (1) the identifying process is susceptible to over-fitting with limited samples of an object, and (2) the sample imbalance between a base (known knowledge) category and a novel category is easy to bias the recognition results.

Few-Shot Learning

Densify Your Labels: Unsupervised Clustering with Bipartite Matching for Weakly Supervised Point Cloud Segmentation

no code implementations11 Dec 2023 Shaobo Xia, Jun Yue, Kacper Kania, Leyuan Fang, Andrea Tagliasacchi, Kwang Moo Yi, Weiwei Sun

We propose a weakly supervised semantic segmentation method for point clouds that predicts "per-point" labels from just "whole-scene" annotations while achieving the performance of recent fully supervised approaches.

Clustering Point Cloud Segmentation +3

SpectralDiff: A Generative Framework for Hyperspectral Image Classification with Diffusion Models

1 code implementation12 Apr 2023 Ning Chen, Jun Yue, Leyuan Fang, Shaobo Xia

The framework consists of a spectral-spatial diffusion module, and an attention-based classification module.

Classification Denoising +1

Dif-Fusion: Towards High Color Fidelity in Infrared and Visible Image Fusion with Diffusion Models

no code implementations19 Jan 2023 Jun Yue, Leyuan Fang, Shaobo Xia, Yue Deng, Jiayi Ma

In specific, instead of converting multi-channel images into single-channel data in existing fusion methods, we create the multi-channel data distribution with a denoising network in a latent space with forward and reverse diffusion process.

Denoising Infrared And Visible Image Fusion

Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives

no code implementations18 Apr 2022 Jun Yue, Leyuan Fang, Pedram Ghamisi, Weiying Xie, Jun Li, Jocelyn Chanussot, Antonio J Plaza

Therefore, remote sensing image understanding often faces the problems of incomplete, inexact, and inaccurate supervised information, which will affect the breadth and depth of remote sensing applications.

Change Detection Image Classification +4

LeafMask: Towards Greater Accuracy on Leaf Segmentation

1 code implementation8 Aug 2021 Ruohao Guo, Liao Qu, Dantong Niu, Zhenbo Li, Jun Yue

In this work, we present the LeafMask neural network, a new end-to-end model to delineate each leaf region and count the number of leaves, with two main components: 1) the mask assembly module merging position-sensitive bases of each predicted box after non-maximum suppression (NMS) and corresponding coefficients to generate original masks; 2) the mask refining module elaborating leaf boundaries from the mask assembly module by the point selection strategy and predictor.

Instance Segmentation Plant Phenotyping +1

Supervised multiview learning based on simultaneous learning of multiview intact and single view classifier

no code implementations9 Jan 2016 Qingjun Wang, Haiyan Lv, Jun Yue, Eugene Mitchell

We define an intact vector for each data point, and a view-conditional transformation matrix for each view, and propose to reconstruct the multiple view feature vectors by the product of the corresponding intact vectors and transformation matrices.

Multiview Learning

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