891 citations · 1.1k across the 27 of their papers we have counts for
7 papers · 2 filters
Active-Passive SimStereo -- Benchmarking the Cross-Generalization Capabilities of Deep Learning-based Stereo Methods
Laurent Jospin, Allen Antony, Lian Xu +3
In stereo vision, self-similar or bland regions can make it difficult to match patches between two images. Active stereo-based methods mitigate this problem by projecting a pseudo-…
Bayesian Learning for Disparity Map Refinement for Semi-Dense Active Stereo Vision
Laurent Valentin Jospin, Hamid Laga, Farid Boussaid +1
A major focus of recent developments in stereo vision has been on how to obtain accurate dense disparity maps in passive stereo vision. Active vision systems enable more accurate e…
A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance
Aref Miri Rekavandi, Lian Xu, Farid Boussaid +3
Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and ident…
Learning Resolution-Adaptive Representations for Cross-Resolution Person Re-Identification
Lin Wu, Lingqiao Liu, Yang Wang +3
The cross-resolution person re-identification (CRReID) problem aims to match low-resolution (LR) query identity images against high resolution (HR) gallery images. It is a challeng…
Pseudo-Pair based Self-Similarity Learning for Unsupervised Person Re-identification
Lin Wu, Deyin Liu, Wenying Zhang +5
Person re-identification (re-ID) is of great importance to video surveillance systems by estimating the similarity between a pair of cross-camera person shorts. Current methods for…
CrossFormer: Cross Spatio-Temporal Transformer for 3D Human Pose Estimation
Mohammed Hassanin, Abdelwahed Khamiss, Mohammed Bennamoun +2
3D human pose estimation can be handled by encoding the geometric dependencies between the body parts and enforcing the kinematic constraints. Recently, Transformer has been adopte…
Multi-class Token Transformer for Weakly Supervised Semantic Segmentation
Lian Xu, Wanli Ouyang, Mohammed Bennamoun +2
This paper proposes a new transformer-based framework to learn class-specific object localization maps as pseudo labels for weakly supervised semantic segmentation (WSSS). Inspired…