🏞 A content-based image retrieval (CBIR) system

A collection of deep learning based RGB-T-Fusion methods, codes, and datasets. The main directions involved are Multispectral Pedestrian Detection, RGB-T Aerial Object Detection, RGB-T Semantic Segmentation, RGB-T Crowd Counting, RGB-T Fusion Tracking.

[ECCV 2020] XingGAN for Person Image Generation

[Neurocomputing 2019] Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion

Damage Identification in Social Media Posts using Multimodal Deep Learning: code and dataset

The implementation of "Towards Faster and Better Federated Learning: A Feature Fusion Approach" (ICIP 2019)

The code of AGCN (Attention-driven Graph Clustering Network), which is accepted by ACM MM 2021.

[Remote Sensing] PyTorch implementation for "Remote Sensing Change Detection Based on Multidirectional Adaptive Feature Fusion and Perceptual Similarity"

Joint detection of Object and its Semantic parts using Attention-based Feature Fusion on PASCAL Parts 2010 dataset

CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors

Bimodal Adaptive Feature Fusion Network for Person Verification

Repository for my paper: Dimensional Speech Emotion Recognition Using Acoustic Features and Word Embeddings using Multitask Learning

Pytorch code for "CoinNet: Deep Ancient Roman Republican Coin Classification via Feature Fusion and Attention."

Attention Based Multi-Instance Thyroid Cytopathological Diagnosis with Multi-Scale Feature Fusion

Implementation of 'Attention-guided Feature Fusion for Small Object Detection'

Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering

A selection of RGB-T object tracking papers and their performance on various benchmarks.

Tri-CNN: A Three Branch Model for Hyperspectral Image Classification

Conditioning and feature fusion methods such as FiLM, Conditional Layer Norm and AdaIN.

The t-SNE visualization and actual query results of the deep feature embeddings for the paper "Supervised Deep Feature Embedding with Hand Crafted Feature" that has been accepted by the IEEE Transactions on Image Processing.