Alternatives and similar repositories for RCIG

Users that are interested in RCIG are comparing it to the libraries listed below

• NUS-HPC-AI-Lab / DATM
  ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
  ☆105Updated last year
• shaoshitong / EDC
  Elucidated Dataset Condensation (NeurIPS 2024)
  ☆20Updated last year
• Yanqing0327 / DREAM
  Efficient Dataset Distillation by Representative Matching
  ☆113Updated last year
• AngusDujw / FTD-distillation
  The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)
  ☆40Updated 2 years ago
• VILA-Lab / SRe2L
  (NeurIPS 2023 spotlight) Large-scale Dataset Distillation/Condensation, 50 IPC (Images Per Class) achieves the highest 60.8% on original …
  ☆136Updated last year
• LINs-lab / RDED
  [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
  ☆81Updated 11 months ago
• shaoshitong / G_VBSM_Dataset_Condensation
  [CVPR2024 highlight] Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching (G-VBSM)
  ☆28Updated last year
• ichbill / LTDD
  Official Implementation of paper "Distilling Long-tailed Datasets" [CVPR 2025]
  ☆19Updated 5 months ago
• NUS-HPC-AI-Lab / DD-Ranking
  Data distillation benchmark
  ☆72Updated 7 months ago
• uitrbn / IDM
  ☆28Updated 2 years ago
• justincui03 / tesla
  ☆30Updated last year
• snu-mllab / Efficient-Dataset-Condensation
  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)
  ☆116Updated 2 years ago
• MIV-XJTU / SPEED
  PyTorch implementation of paper "Sparse Parameterization for Epitomic Dataset Distillation" in NeurIPS 2023.
  ☆20Updated last year
• DataDistillation / DataDAM
  [ICCV 2023] DataDAM: Efficient Dataset Distillation with Attention Matching
  ☆33Updated last year
• Saehyung-Lee / DCC
  This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.
  ☆22Updated 3 years ago
• vimar-gu / MinimaxDiffusion
  [CVPR2024] Efficient Dataset Distillation via Minimax Diffusion
  ☆104Updated last year
• OPTML-Group / ILM-VP
  [CVPR23] "Understanding and Improving Visual Prompting: A Label-Mapping Perspective" by Aochuan Chen, Yuguang Yao, Pin-Yu Chen, Yihua Zha…
  ☆53Updated 2 years ago
• justincui03 / dc_benchmark
  ☆91Updated 3 years ago
• princetonvisualai / multimodal_dataset_distillation
  ☆63Updated last year
• huanranchen / Visualize-Loss-Landscape
  Respect to the input tensor instead of paramters of NN
  ☆21Updated 3 years ago
• yongchaoz / FRePo
  Official Code for Dataset Distillation using Neural Feature Regression (NeurIPS 2022)
  ☆48Updated 3 years ago
• tanganke / peta
  Code for paper "Parameter Efficient Multi-task Model Fusion with Partial Linearization"
  ☆25Updated last year
• ElvishElvis / LCA-on-the-line
  LCA-on-the-line (ICML 2024 Oral)
  ☆13Updated 11 months ago
• yaolu-zjut / DDInterpreter
  ☆15Updated last year
• EnnengYang / AdaMerging
  AdaMerging: Adaptive Model Merging for Multi-Task Learning. ICLR, 2024.
  ☆99Updated last year
• ncsu-dk-lab / Acc-DD
  ☆14Updated 2 years ago
• Huage001 / DatasetFactorization
  PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.
  ☆67Updated 3 years ago
• FarinaMatteo / multiflow
  [CVPR '24] Official implementation of the paper "Multiflow: Shifting Towards Task-Agnostic Vision-Language Pruning".
  ☆23Updated 11 months ago
• harveyhuang18 / EMR_Merging
  [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging
  ☆76Updated 11 months ago
• NUS-HPC-AI-Lab / PAD
  Prioritize Alignment in Dataset Distillation
  ☆21Updated last year