On the Importance of Spatial Relations for Few-shot Action Recognition

On the Importance of Spatial Relations for Few-shot Action Recognition

14 August 2023

Zuxuan Wu

Papers citing "On the Importance of Spatial Relations for Few-shot Action Recognition"

9 / 9 papers shown

Title
A Comprehensive Review of Few-shot Action Recognition Yuyang Wanyan Xiaoshan Yang Weiming Dong Changsheng Xu VLM 74 3 0 20 Jul 2024
DETA: Denoised Task Adaptation for Few-Shot Learning Ji Zhang Lianli Gao Xu Luo Hengtao Shen Jingkuan Song VLM 44 19 0 11 Mar 2023
TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning Linhai Zhuo Yu Fu Jingjing Chen Yixin Cao Yu-Gang Jiang 57 15 0 11 Oct 2022
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning Tu Vu Minh-Thang Luong Quoc V. Le Grady Simon Mohit Iyyer 128 60 0 13 Sep 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 271 2,603 0 04 May 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 317 5,785 0 29 Apr 2021
CrossTransformers: spatially-aware few-shot transfer Carl Doersch Ankush Gupta Andrew Zisserman ViT 215 330 0 22 Jul 2020
Cross Attention Network for Few-shot Classification Rui Hou Hong Chang Bingpeng Ma Shiguang Shan Xilin Chen 204 630 0 17 Oct 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 338 11,684 0 09 Mar 2017