418 citations · 3.5k across the 221 of their papers we have counts for
37 papers · 1 filter
MVTN: Learning Multi-View Transformations for 3D Understanding
Abdullah Hamdi, Faisal AlZahrani, Silvio Giancola +1
Multi-view projection techniques have shown themselves to be highly effective in achieving top-performing results in the recognition of 3D shapes. These methods involve learning ho…
SPARF: Large-Scale Learning of 3D Sparse Radiance Fields from Few Input Images
Abdullah Hamdi, Bernard Ghanem, Matthias Nießner
Recent advances in Neural Radiance Fields (NeRFs) treat the problem of novel view synthesis as Sparse Radiance Field (SRF) optimization using sparse voxels for efficient and fast r…
EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries
Jinjie Mai, Abdullah Hamdi, Silvio Giancola +2
With the recent advances in video and 3D understanding, novel 4D spatio-temporal methods fusing both concepts have emerged. Towards this direction, the Ego4D Episodic Memory Benchm…
PIVOT: Prompting for Video Continual Learning
Andrés Villa, Juan León Alcázar, Motasem Alfarra +5
Modern machine learning pipelines are limited due to data availability, storage quotas, privacy regulations, and expensive annotation processes. These constraints make it difficult…
On Robust Learning from Noisy Labels: A Permutation Layer Approach
Salman Alsubaihi, Mohammed Alkhrashi, Raied Aljadaany +2
The existence of label noise imposes significant challenges (e.g., poor generalization) on the training process of deep neural networks (DNN). As a remedy, this paper introduces a…
SegNeRF: 3D Part Segmentation with Neural Radiance Fields
Jesus Zarzar, Sara Rojas, Silvio Giancola +1
Recent advances in Neural Radiance Fields (NeRF) boast impressive performances for generative tasks such as novel view synthesis and 3D reconstruction. Methods based on neural radi…
Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training
Ling Yang, Zhilin Huang, Yang Song +6
Generating images from graph-structured inputs, such as scene graphs, is uniquely challenging due to the difficulty of aligning nodes and connections in graphs with objects and the…
Estimating more camera poses for ego-centric videos is essential for VQ3D
Jinjie Mai, Chen Zhao, Abdullah Hamdi +2
Visual queries 3D localization (VQ3D) is a task in the Ego4D Episodic Memory Benchmark. Given an egocentric video, the goal is to answer queries of the form "Where did I last see o…
SimCS: Simulation for Domain Incremental Online Continual Segmentation
Motasem Alfarra, Zhipeng Cai, Adel Bibi +2
Continual Learning is a step towards lifelong intelligence where models continuously learn from recently collected data without forgetting previous knowledge. Existing continual le…
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…
Re^2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization
Chen Zhao, Shuming Liu, Karttikeya Mangalam +1
Temporal action localization (TAL) requires long-form reasoning to predict actions of various durations and complex content. Given limited GPU memory, training TAL end to end (i.e.…
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…
Decoupled Mixup for Generalized Visual Recognition
Haozhe Liu, Wentian Zhang, Jinheng Xie +7
Convolutional neural networks (CNN) have demonstrated remarkable performance when the training and testing data are from the same distribution. However, such trained CNN models oft…
SoccerNet 2022 Challenges Results
Silvio Giancola, Anthony Cioppa, Adrien Deliège +91
The SoccerNet 2022 challenges were the second annual video understanding challenges organized by the SoccerNet team. In 2022, the challenges were composed of 6 vision-based tasks:…
Generalizability of Adversarial Robustness Under Distribution Shifts
Kumail Alhamoud, Hasan Abed Al Kader Hammoud, Motasem Alfarra +1
Recent progress in empirical and certified robustness promises to deliver reliable and deployable Deep Neural Networks (DNNs). Despite that success, most existing evaluations of DN…
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…
Egocentric Video-Language Pretraining @ Ego4D Challenge 2022
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
In this report, we propose a video-language pretraining (VLP) based solution \cite{kevin2022egovlp} for four Ego4D challenge tasks, including Natural Language Query (NLQ), Moment Q…
Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding
Guocheng Qian, Abdullah Hamdi, Xingdi Zhang +1
While Transformers have achieved impressive success in natural language processing and computer vision, their performance on 3D point clouds is relatively poor. This is mainly due…
Combating Mode Collapse in GANs via Manifold Entropy Estimation
Haozhe Liu, Bing Li, Haoqian Wu +5
Generative Adversarial Networks (GANs) have shown compelling results in various tasks and applications in recent years. However, mode collapse remains a critical problem in GANs. I…
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
Guocheng Qian, Yuchen Li, Houwen Peng +4
PointNet++ is one of the most influential neural architectures for point cloud understanding. Although the accuracy of PointNet++ has been largely surpassed by recent networks such…
Certified Robustness in Federated Learning
Motasem Alfarra, Juan C. Pérez, Egor Shulgin +2
Federated learning has recently gained significant attention and popularity due to its effectiveness in training machine learning models on distributed data privately. However, as…
Egocentric Video-Language Pretraining
Kevin Qinghong Lin, Alex Jinpeng Wang, Mattia Soldan +13
Video-Language Pretraining (VLP), which aims to learn transferable representation to advance a wide range of video-text downstream tasks, has recently received increasing attention…
UnrealNAS: Can We Search Neural Architectures with Unreal Data?
Zhen Dong, Kaicheng Zhou, Guohao Li +5
Neural architecture search (NAS) has shown great success in the automatic design of deep neural networks (DNNs). However, the best way to use data to search network architectures i…
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…