28 citations · 68 across the 15 of their papers we have counts for
16 papers
Mindstorms in Natural Language-Based Societies of Mind
Mingchen Zhuge, Haozhe Liu, Francesco Faccio +23
Both Minsky's "society of mind" and Schmidhuber's "learning to think" inspire diverse societies of large multimodal neural networks (NNs) that solve problems by interviewing each o…
Boundary-Denoising for Video Activity Localization
Mengmeng Xu, Mattia Soldan, Jialin Gao +3
Video activity localization aims at understanding the semantic content in long untrimmed videos and retrieving actions of interest. The retrieved action with its start and end loca…
Multi-Modal Few-Shot Temporal Action Detection
Sauradip Nag, Mengmeng Xu, Xiatian Zhu +4
Few-shot (FS) and zero-shot (ZS) learning are two different approaches for scaling temporal action detection (TAD) to new classes. The former adapts a pretrained vision model to a…
Where is my Wallet? Modeling Object Proposal Sets for Egocentric Visual Query Localization
Mengmeng Xu, Yanghao Li, Cheng-Yang Fu +3
This paper deals with the problem of localizing objects in image and video datasets from visual exemplars. In particular, we focus on the challenging problem of egocentric visual q…
Negative Frames Matter in Egocentric Visual Query 2D Localization
Mengmeng Xu, Cheng-Yang Fu, Yanghao Li +3
The recently released Ego4D dataset and benchmark significantly scales and diversifies the first-person visual perception data. In Ego4D, the Visual Queries 2D Localization task ai…
ETAD: Training Action Detection End to End on a Laptop
Shuming Liu, Mengmeng Xu, Chen Zhao +2
Temporal action detection (TAD) with end-to-end training often suffers from the pain of huge demand for computing resources due to long video duration. In this work, we propose an…
Contrastive Language-Action Pre-training for Temporal Localization
Mengmeng Xu, Erhan Gundogdu, Maksim Lapin +3
Long-form video understanding requires designing approaches that are able to temporally localize activities or language. End-to-end training for such tasks is limited by the comput…
SegTAD: Precise Temporal Action Detection via Semantic Segmentation
Chen Zhao, Merey Ramazanova, Mengmeng Xu +1
Temporal action detection (TAD) is an important yet challenging task in video analysis. Most existing works draw inspiration from image object detection and tend to reformulate it…
On Mixing Times of Metropolized Algorithm With Optimization Step (MAO) : A New Framework
EL Mahdi Khribch, George Deligiannidis, Daniel Paulin
In this paper, we consider sampling from a class of distributions with thin tails supported on and make two primary contributions. First, we propose a new Metropoliz…
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Kristen Grauman, Andrew Westbury, Eugene Byrne +82
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outd…
Low-Fidelity End-to-End Video Encoder Pre-training for Temporal Action Localization
Mengmeng Xu, Juan-Manuel Perez-Rua, Xiatian Zhu +2
Temporal action localization (TAL) is a fundamental yet challenging task in video understanding. Existing TAL methods rely on pre-training a video encoder through action classifica…
Boundary-sensitive Pre-training for Temporal Localization in Videos
Mengmeng Xu, Juan-Manuel Perez-Rua, Victor Escorcia +5
Many video analysis tasks require temporal localization thus detection of content changes. However, most existing models developed for these tasks are pre-trained on general video…
VLG-Net: Video-Language Graph Matching Network for Video Grounding
Mattia Soldan, Mengmeng Xu, Sisi Qu +2
Grounding language queries in videos aims at identifying the time interval (or moment) semantically relevant to a language query. The solution to this challenging task demands unde…
LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks
Guohao Li, Mengmeng Xu, Silvio Giancola +2
Point cloud architecture design has become a crucial problem for 3D deep learning. Several efforts exist to manually design architectures with high accuracy in point cloud tasks su…
Learning Heat Diffusion for Network Alignment
Sisi Qu, Mengmeng Xu, Bernard Ghanem +1
Networks are abundant in the life sciences. Outstanding challenges include how to characterize similarities between networks, and in extension how to integrate information across n…
G-TAD: Sub-Graph Localization for Temporal Action Detection
Mengmeng Xu, Chen Zhao, David S. Rojas +2
Temporal action detection is a fundamental yet challenging task in video understanding. Video context is a critical cue to effectively detect actions, but current works mainly focu…