288 citations · 453 across the 42 of their papers we have counts for
7 papers · 1 filter
Video Prediction by Efficient Transformers
Xi Ye, Guillaume-Alexandre Bilodeau
Video prediction is a challenging computer vision task that has a wide range of applications. In this work, we present a new family of Transformer-based models for video prediction…
A unified model for continuous conditional video prediction
Xi Ye, Guillaume-Alexandre Bilodeau
Different conditional video prediction tasks, like video future frame prediction and video frame interpolation, are normally solved by task-related models even though they share ma…
Improving tracking with a tracklet associator
Rémi Nahon, Guillaume-Alexandre Bilodeau, Gilles Pesant
Multiple object tracking (MOT) is a task in computer vision that aims to detect the position of various objects in videos and to associate them to a unique identity. We propose an…
4D-MultispectralNet: Multispectral Stereoscopic Disparity Estimation using Human Masks
Philippe Duplessis-Guindon, Guillaume-Alexandre Bilodeau
Multispectral stereoscopy is an emerging field. A lot of work has been done in classical stereoscopy, but multispectral stereoscopy is not studied as frequently. This type of stere…
ActAR: Actor-Driven Pose Embeddings for Video Action Recognition
Soufiane Lamghari, Guillaume-Alexandre Bilodeau, Nicolas Saunier
Human action recognition (HAR) in videos is one of the core tasks of video understanding. Based on video sequences, the goal is to recognize actions performed by humans. While HAR…
Transformers for 1D Signals in Parkinson's Disease Detection from Gait
Duc Minh Dimitri Nguyen, Mehdi Miah, Guillaume-Alexandre Bilodeau +1
This paper focuses on the detection of Parkinson's disease based on the analysis of a patient's gait. The growing popularity and success of Transformer networks in natural language…
VPTR: Efficient Transformers for Video Prediction
Xi Ye, Guillaume-Alexandre Bilodeau
In this paper, we propose a new Transformer block for video future frames prediction based on an efficient local spatial-temporal separation attention mechanism. Based on this new…