Alternatives and similar repositories for bias:

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

• liuxingbin / dbot
  [ICLR2024] Exploring Target Representations for Masked Autoencoders
  ☆52Updated last year
• Haochen-Wang409 / DropPos
  [NeurIPS'23] DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
  ☆61Updated 9 months ago
• zejiangh / MILAN
  PyTorch implementation of the paper "MILAN: Masked Image Pretraining on Language Assisted Representation" https://arxiv.org/pdf/2208.0604…
  ☆82Updated 2 years ago
• UCSC-VLAA / DMAE
  [CVPR 2023] This repository includes the official implementation our paper "Masked Autoencoders Enable Efficient Knowledge Distillers"
  ☆103Updated last year
• hunto / DiffKD
  Official implementation for paper "Knowledge Diffusion for Distillation", NeurIPS 2023
  ☆79Updated last year
• OpenDriveLab / maskalign
  [CVPR 2023] Official repository for paper "Stare at What You See: Masked Image Modeling without Reconstruction"
  ☆69Updated last year
• CVMI-Lab / SlotCon
  (NeurIPS 2022) Self-Supervised Visual Representation Learning with Semantic Grouping
  ☆95Updated last year
• Paranioar / UniPT
  [CVPR2024] The code of "UniPT: Universal Parallel Tuning for Transfer Learning with Efficient Parameter and Memory"
  ☆66Updated 4 months ago
• Jiahao000 / MFM
  [ICLR 2023] Masked Frequency Modeling for Self-Supervised Visual Pre-Training
  ☆70Updated last year
• dongzelian / SSF
  [NeurIPS'22] This is an official implementation for "Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning".
  ☆176Updated last year
• ZhangYuanhan-AI / visual_prompt_retrieval
  [NeurIPS2023] Official implementation and model release of the paper "What Makes Good Examples for Visual In-Context Learning?"
  ☆171Updated 11 months ago
• ChangyaoTian / VL-LTR
  VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition
  ☆66Updated 2 years ago
• Waybaba / DIGA
  Official implementation for Dynamically Instance-Guided Adaptation: A Backward-free Approach for Test-Time Domain Adaptive Semantic Segme…
  ☆11Updated 10 months ago
• Gorilla-Lab-SCUT / TTAC
  [NeurIPS 2022] Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering
  ☆45Updated last year
• OliverRensu / DeepMIM
  ☆52Updated last year
• yossigandelsman / test_time_training_mae
  The official github repo for "Test-Time Training with Masked Autoencoders"
  ☆80Updated last year
• ggjy / DeLVM
  ☆114Updated 8 months ago
• LeapLabTHU / Deep-Incubation
  Code release for Deep Incubation (https://arxiv.org/abs/2212.04129)
  ☆91Updated last year
• ziplab / SPT
  [ICCV 2023 oral] This is the official repository for our paper: ''Sensitivity-Aware Visual Parameter-Efficient Fine-Tuning''.
  ☆65Updated last year
• mzhaoshuai / RLCF
  [ICLR 2024] Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models.
  ☆67Updated 6 months ago
• junchen14 / LoMaR
  LoMaR (Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction)
  ☆62Updated 2 years ago
• gaopengcuhk / BALLAD
  ☆59Updated 2 years ago
• zhangq327 / U-MAE
  Official Code for NeurIPS 2022 Paper: How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders
  ☆57Updated last year
• showlab / datacentric.vlp
  Compress conventional Vision-Language Pre-training data
  ☆49Updated last year
• eric-ai-lab / PEViT
  Official implementation of AAAI 2023 paper "Parameter-efficient Model Adaptation for Vision Transformers"
  ☆100Updated last year
• JieShibo / PETL-ViT
  [ICCV 2023 & AAAI 2023] Binary Adapters & FacT, [Tech report] Convpass
  ☆175Updated last year
• LightDXY / BootMAE
  ECCV2022,Bootstrapped Masked Autoencoders for Vision BERT Pretraining
  ☆97Updated 2 years ago
• ZrrSkywalker / CaFo
  [CVPR 2023] Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners
  ☆41Updated last year
• DavidYanAnDe / ARC
  ☆32Updated last year
• Leiyi-Hu / mona
  The official implementation of "Adapter is All You Need for Tuning Visual Tasks".
  ☆77Updated 5 months ago