44 citations · 151 across the 13 of their papers we have counts for
13 papers
UnLoc: A Unified Framework for Video Localization Tasks
Shen Yan, Xuehan Xiong, Arsha Nagrani +5
While large-scale image-text pretrained models such as CLIP have been used for multiple video-level tasks on trimmed videos, their use for temporal localization in untrimmed videos…
End-to-End Spatio-Temporal Action Localisation with Video Transformers
Alexey Gritsenko, Xuehan Xiong, Josip Djolonga +5
The most performant spatio-temporal action localisation models use external person proposals and complex external memory banks. We propose a fully end-to-end, purely-transformer ba…
Beyond Transfer Learning: Co-finetuning for Action Localisation
Anurag Arnab, Xuehan Xiong, Alexey Gritsenko +6
Transfer learning is the predominant paradigm for training deep networks on small target datasets. Models are typically pretrained on large ``upstream'' datasets for classification…
M&M Mix: A Multimodal Multiview Transformer Ensemble
Xuehan Xiong, Anurag Arnab, Arsha Nagrani +1
This report describes the approach behind our winning solution to the 2022 Epic-Kitchens Action Recognition Challenge. Our approach builds upon our recent work, Multiview Transform…
Multiview Transformers for Video Recognition
Shen Yan, Xuehan Xiong, Anurag Arnab +4
Video understanding requires reasoning at multiple spatiotemporal resolutions -- from short fine-grained motions to events taking place over longer durations. Although transformer…
Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts
Kunpeng Li, Zizhao Zhang, Guanhang Wu +5
Learning visual knowledge from massive weakly-labeled web videos has attracted growing research interests thanks to the large corpus of easily accessible video data on the Internet…
Spatial-Temporal Alignment Network for Action Recognition and Detection
Junwei Liang, Liangliang Cao, Xuehan Xiong +2
This paper studies how to introduce viewpoint-invariant feature representations that can help action recognition and detection. Although we have witnessed great progress of action…
PERF-Net: Pose Empowered RGB-Flow Net
Yinxiao Li, Zhichao Lu, Xuehan Xiong +1
In recent years, many works in the video action recognition literature have shown that two stream models (combining spatial and temporal input streams) are necessary for achieving…
AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification
Xiaofang Wang, Xuehan Xiong, Maxim Neumann +5
Convolutional operations have two limitations: (1) do not explicitly model where to focus as the same filter is applied to all the positions, and (2) are unsuitable for modeling lo…
An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints
Zhe Li, Xuehan Xiong, Zhou Ren +3
Recently, there emerged revived interests of designing automatic programs (e.g., using genetic/evolutionary algorithms) to optimize the structure of Convolutional Neural Networks (…
Efficient Video Object Segmentation via Network Modulation
Linjie Yang, Yanran Wang, Xuehan Xiong +2
Video object segmentation targets at segmenting a specific object throughout a video sequence, given only an annotated first frame. Recent deep learning based approaches find it ef…
Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision
Xuehan Xiong, Fernando De la Torre
Many computer vision problems (e.g., camera calibration, image alignment, structure from motion) are solved with nonlinear optimization methods. It is generally accepted that secon…
Bayesian Optimal Active Search and Surveying
Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong +2
We consider two active binary-classification problems with atypical objectives. In the first, active search, our goal is to actively uncover as many members of a given class as pos…