On the Viability of Monocular Depth Pre-training for Semantic Segmentation

26 March 2022

Papers citing "On the Viability of Monocular Depth Pre-training for Semantic Segmentation"

6 / 6 papers shown

Title
Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data Lihe Yang Bingyi Kang Zilong Huang Xiaogang Xu Jiashi Feng Hengshuang Zhao VLM 139 681 0 19 Jan 2024
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks Micah Goldblum Hossein Souri Renkun Ni Manli Shu Viraj Prabhu ... Adrien Bardes Judy Hoffman Ramalingam Chellappa Andrew Gordon Wilson Tom Goldstein VLM 68 62 0 30 Oct 2023
AugUndo: Scaling Up Augmentations for Unsupervised Depth Completion Yangchao Wu Tian Yu Liu Hyoungseob Park Stefano Soatto Dong Lao Alex Wong 35 4 0 15 Oct 2023
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
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