418 citations · 3.5k across the 221 of their papers we have counts for
20 papers · 1 filter
Spatio-temporal Relation Modeling for Few-shot Action Recognition
Anirudh Thatipelli, Sanath Narayan, Salman Khan +3
We propose a novel few-shot action recognition framework, STRM, which enhances class-specific feature discriminability while simultaneously learning higher-order temporal represent…
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…
MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions
Mattia Soldan, Alejandro Pardo, Juan León Alcázar +4
The recent and increasing interest in video-language research has driven the development of large-scale datasets that enable data-intensive machine learning techniques. In comparis…
Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding
Abdullah Hamdi, Silvio Giancola, Bernard Ghanem
Multi-view projection methods have demonstrated promising performance on 3D understanding tasks like 3D classification and segmentation. However, it remains unclear how to combine…
ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
Guocheng Qian, Hasan Abed Al Kader Hammoud, Guohao Li +2
Access to 3D point cloud representations has been widely facilitated by LiDAR sensors embedded in various mobile devices. This has led to an emerging need for fast and accurate poi…
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…
Learning to Cut by Watching Movies
Alejandro Pardo, Fabian Caba Heilbron, Juan León Alcázar +2
Video content creation keeps growing at an incredible pace; yet, creating engaging stories remains challenging and requires non-trivial video editing expertise. Many video editing…
MovieCuts: A New Dataset and Benchmark for Cut Type Recognition
Alejandro Pardo, Fabian Caba Heilbron, Juan León Alcázar +2
Understanding movies and their structural patterns is a crucial task in decoding the craft of video editing. While previous works have developed tools for general analysis, such as…
Check Your Other Door! Creating Backdoor Attacks in the Frequency Domain
Hasan Abed Al Kader Hammoud, Bernard Ghanem
Deep Neural Networks (DNNs) are ubiquitous and span a variety of applications ranging from image classification to real-time object detection. As DNN models become more sophisticat…
Enhancing Adversarial Robustness via Test-time Transformation Ensembling
Juan C. Pérez, Motasem Alfarra, Guillaume Jeanneret +4
Deep learning models are prone to being fooled by imperceptible perturbations known as adversarial attacks. In this work, we study how equipping models with Test-time Transformatio…
ANCER: Anisotropic Certification via Sample-wise Volume Maximization
Francisco Eiras, Motasem Alfarra, M. Pawan Kumar +4
Randomized smoothing has recently emerged as an effective tool that enables certification of deep neural network classifiers at scale. All prior art on randomized smoothing has foc…
DeformRS: Certifying Input Deformations with Randomized Smoothing
Motasem Alfarra, Adel Bibi, Naeemullah Khan +2
Deep neural networks are vulnerable to input deformations in the form of vector fields of pixel displacements and to other parameterized geometric deformations e.g. translations, r…
APES: Audiovisual Person Search in Untrimmed Video
Juan Leon Alcazar, Long Mai, Federico Perazzi +4
Humans are arguably one of the most important subjects in video streams, many real-world applications such as video summarization or video editing workflows often require the autom…
Training Graph Neural Networks with 1000 Layers
Guohao Li, Matthias Müller, Bernard Ghanem +1
Deep graph neural networks (GNNs) have achieved excellent results on various tasks on increasingly large graph datasets with millions of nodes and edges. However, memory complexity…
SCTN: Sparse Convolution-Transformer Network for Scene Flow Estimation
Bing Li, Cheng Zheng, Silvio Giancola +1
We propose a novel scene flow estimation approach to capture and infer 3D motions from point clouds. Estimating 3D motions for point clouds is challenging, since a point cloud is u…
Camera Calibration and Player Localization in SoccerNet-v2 and Investigation of their Representations for Action Spotting
Anthony Cioppa, Adrien Deliège, Floriane Magera +4
Soccer broadcast video understanding has been drawing a lot of attention in recent years within data scientists and industrial companies. This is mainly due to the lucrative potent…
Temporally-Aware Feature Pooling for Action Spotting in Soccer Broadcasts
Silvio Giancola, Bernard Ghanem
Toward the goal of automatic production for sports broadcasts, a paramount task consists in understanding the high-level semantic information of the game in play. For instance, rec…
AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
Bing Li, Yuanlue Zhu, Yitong Wang +3
In this paper, we propose a novel framework to translate a portrait photo-face into an anime appearance. Our aim is to synthesize anime-faces which are style-consistent with a give…
Combating Adversaries with Anti-Adversaries
Motasem Alfarra, Juan C. Pérez, Ali Thabet +3
Deep neural networks are vulnerable to small input perturbations known as adversarial attacks. Inspired by the fact that these adversaries are constructed by iteratively minimizing…
MAAS: Multi-modal Assignation for Active Speaker Detection
Juan León-Alcázar, Fabian Caba Heilbron, Ali Thabet +1
Active speaker detection requires a solid integration of multi-modal cues. While individual modalities can approximate a solution, accurate predictions can only be achieved by expl…