2 citations · 5 across the 6 of their papers we have counts for
8 papers
Learning Structured Visual Compositional Representations for Weakly Supervised Referring Expression Comprehension
Lian Xu, Mohammed Bennamoun, Farid Boussaid +3
Referring expression comprehension (REC) aims to localize the object in an image described by natural language. In Weakly supervised REC (WREC), existing approaches primarily opera…
SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition
Yanan Liu, Anqi Zhu, Jingmin Zhu +6
Skeleton-based action recognition aims to understand human behaviors from body joint sequences and is especially challenging in the one-shot setting, where only a single labeled ex…
SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition
Ning Wang, Tieyue Wu, Naeha Sharif +5
Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typ…
Controllable Complex Human Motion Video Generation via Text-to-Skeleton Cascades
Ashkan Taghipour, Morteza Ghahremani, Zinuo Li +3
Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally…
A Survey on Deep Learning Techniques for Stereo-based Depth Estimation
Hamid Laga, Laurent Valentin Jospin, Farid Boussaid +1
Estimating depth from RGB images is a long-standing ill-posed problem, which has been explored for decades by the computer vision, graphics, and machine learning communities. Among…
Exploiting Layerwise Convexity of Rectifier Networks with Sign Constrained Weights
Senjian An, Farid Boussaid, Mohammed Bennamoun +1
By introducing sign constraints on the weights, this paper proposes sign constrained rectifier networks (SCRNs), whose training can be solved efficiently by the well known majoriza…