Teaching Matters: Investigating the Role of Supervision in Vision
Transformers

Teaching Matters: Investigating the Role of Supervision in Vision Transformers

7 December 2022

Abhinav Shrivastava

Papers citing "Teaching Matters: Investigating the Role of Supervision in Vision Transformers"

9 / 9 papers shown

Title
Can Masked Autoencoders Also Listen to Birds? Lukas Rauch Ilyass Moummad René Heinrich Alexis Joly Bernhard Sick Christoph Scholz 27 0 0 17 Apr 2025
Perception Encoder: The best visual embeddings are not at the output of the network Daniel Bolya Po-Yao (Bernie) Huang Peize Sun Jang Hyun Cho Andrea Madotto ... Shiyu Dong Nikhila Ravi Daniel Li Piotr Dollár Christoph Feichtenhofer ObjD VOS 103 0 0 17 Apr 2025
MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations Benedikt Alkin Lukas Miklautz Sepp Hochreiter Johannes Brandstetter VLM 60 8 0 24 Feb 2025
Self-Explainable Affordance Learning with Embodied Caption Zhipeng Zhang Zhimin Wei Guolei Sun Peng Wang Luc Van Gool 40 2 0 08 Apr 2024
Beyond Supervised vs. Unsupervised: Representative Benchmarking and Analysis of Image Representation Learning M. Gwilliam Abhinav Shrivastava SSL 71 19 1 16 Jun 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Localizing Objects with Self-Supervised Transformers and no Labels Oriane Siméoni Gilles Puy Huy V. Vo Simon Roburin Spyros Gidaris Andrei Bursuc P. Pérez Renaud Marlet Jean Ponce ViT 170 195 0 29 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,359 0 09 Mar 2020