he-y / you-only-condense-onceLinks
You Only Condense Once: Two Rules for Pruning Condensed Datasets (NeurIPS 2023)
☆15Updated last year
Alternatives and similar repositories for you-only-condense-once
Users that are interested in you-only-condense-once are comparing it to the libraries listed below
Sorting:
- The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)☆40Updated 2 years ago
- [ICCV 2023] DataDAM: Efficient Dataset Distillation with Attention Matching☆34Updated last year
- PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.☆66Updated 2 years ago
- An open-world scenario domain generalization code base☆26Updated 2 years ago
- ☆27Updated 2 years ago
- [IJCV2025] https://arxiv.org/abs/2304.04521☆15Updated 7 months ago
- PyTorch implementation of paper "Sparse Parameterization for Epitomic Dataset Distillation" in NeurIPS 2023.☆21Updated last year
- Official PyTorch implementation of "Multisize Dataset Condensation" (ICLR'24 Oral)☆14Updated last year
- [ICML2023] Revisiting Data-Free Knowledge Distillation with Poisoned Teachers☆23Updated last year
- TF-FD☆20Updated 2 years ago
- ☆26Updated last year
- [ICML 2023] "Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability"☆18Updated 2 years ago
- [TMLR'24] This repository includes the official implementation our paper "Unleashing the Power of Visual Prompting At the Pixel Level"☆41Updated last year
- Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"☆40Updated 2 years ago
- ☆15Updated last year
- ECCV24, NeurIPS24, Benchmarking Generalized Out-of-Distribution Detection with Vision-Language Models☆28Updated 8 months ago
- ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection☆24Updated last year
- Switchable Online Knowledge Distillation☆19Updated 10 months ago
- Code for ICML 2023 paper "When and How Does Known Class Help Discover Unknown Ones? Provable Understandings Through Spectral Analysis"☆13Updated 2 years ago
- [NeurIPS 2024] WATT: Weight Average Test-Time Adaptation of CLIP☆53Updated 11 months ago
- [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective☆37Updated 2 years ago
- [CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zha…☆53Updated last year
- Pytorch implementation of our paper accepted by ECCV2022 -- Knowledge Condensation Distillation https://arxiv.org/abs/2207.05409☆30Updated 2 years ago
- Pytorch implementation of: "Continual Semantic Segmentation via Structure Preserving and Projected Feature Alignment", ECCV22☆11Updated 3 years ago
- ☆23Updated last year
- ☆12Updated last year
- [ECCV 2022] "Adversarial Contrastive Learning via Asymmetric InfoNCE"☆24Updated 2 years ago
- [CVPR'24] Validation-free few-shot adaptation of CLIP, using a well-initialized Linear Probe (ZSLP) and class-adaptive constraints (CLAP)…☆75Updated 2 months ago
- Official pytorch implementation of NeurIPS 2022 paper, TokenMixup☆48Updated 2 years ago
- An Efficient Dataset Condensation Plugin and Its Application to Continual Learning. NeurIPS, 2023.☆11Updated last year