LU's repositories
Awesome-Efficient-AI-for-Large-Scale-Models
Paper survey of efficient computation for large scale models.
CAT-KD
Class Attention Transfer Based Knowledge Distillation
Conference-Accepted-Paper-List
Some Conferences' accepted paper lists (including AI, ML, Robotic)
Deep-Class-Incremental-Learning
The code repository for "Deep Class-Incremental Learning: A Survey" in PyTorch.
Dual-Cross
Cross-Domain and Cross-Modal Knowledge Distillation in Domain Adaptation for 3D Semantic Segmentation (ACMMM2022)
ECON
[CVPR 2023] ECON: Explicit Clothed humans Obtained from Normals
FlatTrajectoryDistillation_FTD
The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)
GaussianDistillation
Data-free knowledge distillation using Gaussian noise (NeurIPS paper)
HieraSeg
CVPR2022 - Deep Hierarchical Semantic Segmentation - A structured, pixel-wise description of visual scenes in terms of the class hierarchy.
KDSR
This project is the official implementation of 'Knowledge Distillation based Degradation Estimation for Blind Super-Resolution', ICLR2023
Multi-Level-Logit-Distillation
Code for 'Multi-level Logit Distillation' (CVPR2023)
OKDPH
OKDPH： Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation
online-hyperparameter-optimization
PyTorch implementation of "Online Hyperparameter Optimization for Class-Incremental Learning" (AAAI 2023)
PD-Quant
[CVPR 2023] PD-Quant: Post-Training Quantization Based on Prediction Difference Metric
Point-NN
[CVPR 2023] Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis
prompt-in-context-learning
Awesome resources for in-context learning and prompt engineering: Mastery of the LLMs such as ChatGPT, GPT-3, and FlanT5, with up-to-date and cutting-edge updates.
SadTalker
（CVPR 2023）SadTalker：Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation
segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
SMD
Pytorch implementation of 'Improving Self-supervised Lightweight Model Learning via Hard-aware Metric Distillation. In ECCV 2022'
superclass-FSIS
This is the official implementation of the paper "Instance-level Few-shot Learning with Class Hierarchy Mining"
Torch-Pruning
[CVPR-2023] Towards Any Structural Pruning
XDED
Official PyTorch implementation of "Cross-Domain Ensemble Distillation for Domain Generalization" (ECCV 2022)