CVMI-Lab / SyntheticData
Is synthetic data from generative models ready for image recognition?
☆176Updated last year
Related projects ⓘ
Alternatives and complementary repositories for SyntheticData
- [NeurIPS2023] Official implementation and model release of the paper "What Makes Good Examples for Visual In-Context Learning?"☆166Updated 8 months ago
- Official implementation and data release of the paper "Visual Prompting via Image Inpainting".☆301Updated last year
- [TPAMI] Searching prompt modules for parameter-efficient transfer learning.☆224Updated 11 months ago
- Augmenting with Language-guided Image Augmentation (ALIA)☆63Updated last year
- [NeurIPS'22] This is an official implementation for "Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning".☆173Updated last year
- [ICCV 2023] Prompt-aligned Gradient for Prompt Tuning☆151Updated last year
- Exploring Visual Prompts for Adapting Large-Scale Models☆267Updated 2 years ago
- [ICLR'23 Oral] Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching☆251Updated last year
- [CVPR 2023] This repository includes the official implementation our paper "Masked Autoencoders Enable Efficient Knowledge Distillers"☆99Updated last year
- Official PyTorch implementation for "Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels"☆80Updated 10 months ago
- Official implementation for paper "Knowledge Diffusion for Distillation", NeurIPS 2023☆76Updated 9 months ago
- Official repository of "Back to Source: Diffusion-Driven Test-Time Adaptation"☆71Updated 11 months ago
- Efficient Dataset Distillation by Representative Matching☆107Updated 8 months ago
- Test-time Prompt Tuning (TPT) for zero-shot generalization in vision-language models (NeurIPS 2022))☆145Updated 2 years ago
- ☆93Updated 6 months ago
- ☆58Updated 2 years ago
- This repo is the official implementation of UPL (Unsupervised Prompt Learning for Vision-Language Models).☆106Updated 2 years ago
- [ICLR 2024] Real-Fake: Effective Training Data Synthesis Through Distribution Matching☆72Updated 11 months ago
- ☆105Updated last year
- [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion☆80Updated 8 months ago
- The repository of Expanding Small-Scale Datasets with Guided Imagination (NeurIPS 2023).☆76Updated 10 months ago
- Code for Finetune like you pretrain: Improved finetuning of zero-shot vision models☆90Updated last year
- source code for NeurIPS'23 paper "Dream the Impossible: Outlier Imagination with Diffusion Models"☆62Updated 3 weeks ago
- ECCV2022,Bootstrapped Masked Autoencoders for Vision BERT Pretraining☆98Updated 2 years ago
- Diffusion-TTA improves pre-trained discriminative models such as image classifiers or segmentors using pre-trained generative models.☆57Updated 8 months ago
- The collection of awesome papers on alignment of diffusion models.☆53Updated this week
- [NeurIPS 2023] Text data, code and pre-trained models for paper "Improving CLIP Training with Language Rewrites"☆260Updated 10 months ago
- Code for "Training on Thin Air: Improve Image Classification with Generated Data"☆43Updated last year
- ☆41Updated last year
- [ECCV 2024] Official PyTorch implementation of DreamLIP: Language-Image Pre-training with Long Captions☆106Updated 3 weeks ago