Stars
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition
MeTAN: Metaphoric Temporal Attention Network for depression detection on Social Media
A collection of datasets for depression detection/ modelling from social media data
[ECCV 2022] TinyViT: Fast Pretraining Distillation for Small Vision Transformers (https://github.com/microsoft/Cream/tree/main/TinyViT)
[CVPR2024] ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts
Official Code for "Can Language Beat Numerical Regression? Language-Based Multimodal Trajectory Prediction (CVPR 2024)"
基于Clash Core 制作的Clash For Linux备份仓库 A Clash For Linux Backup Warehouse Based on Clash Core
Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"
IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks
BERT-XDD is a deep learning methodology for effective and interpretable depression detection from social media posts.
Use sentimental analysis and machine learning algorithms to predict the mental health of users using their social media posts.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
The code relevant to my dissertation for MSc Computer Science (Artificial Intelligence). NOTE: This code is not entirely my own, and is based off of several code repositorys, principally the AVEC20…
[ACL 2024] Official PyTorch code for extracting features and training downstream models with emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation
项目使用:https://github.com/ix64/unlock-music和https://github.com/NetDimension/NanUI进行封装方便在本地使用
在浏览器中解锁加密的音乐文件。原仓库: 1. https://github.com/unlock-music/unlock-music ;2. https://git.unlock-music.dev/um/web
Exploring attention weights in transformer-based models with linguistic knowledge.
eeric / insightface
Forked from deepinsight/insightfaceFace Analysis Project on MXNet
A landmark-driven method on Facial Expression Recognition (FER)