Learning to Count without Annotations

17 July 2023

Papers citing "Learning to Count without Annotations"

7 / 7 papers shown

Title
Learning to Count Anything: Reference-less Class-agnostic Counting with Weak Supervision Michael A. Hobley V. Prisacariu 39 23 0 20 May 2022
Few-shot Object Counting with Similarity-Aware Feature Enhancement Zhiyuan You Kai Yang Wenhan Luo X. Lu Lei Cui Xinyi Le 31 43 0 22 Jan 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 161 195 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
Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation Golnaz Ghiasi Yin Cui A. Srinivas Rui Qian Tsung-Yi Lin E. D. Cubuk Quoc V. Le Barret Zoph ISeg 223 835 0 13 Dec 2020
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 279 39,083 0 01 Sep 2014