3 citations · 7 across the 18 of their papers we have counts for
6 papers · 1 filter
Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning
Remco F. Leijenaar, Hamidreza Kasaei
Learning semantically meaningful representations from unstructured 3D point clouds remains a central challenge in computer vision, especially in the absence of large-scale labeled…
LM-MCVT: A Lightweight Multi-modal Multi-view Convolutional-Vision Transformer Approach for 3D Object Recognition
Songsong Xiong, Hamidreza Kasaei
In human-centered environments such as restaurants, homes, and warehouses, robots often face challenges in accurately recognizing 3D objects. These challenges stem from the complex…
3D Feature Distillation with Object-Centric Priors
Georgios Tziafas, Yucheng Xu, Zhibin Li +1
Grounding natural language to the physical world is a ubiquitous topic with a wide range of applications in computer vision and robotics. Recently, 2D vision-language models such a…
Fine-grained 3D object recognition: an approach and experiments
Junhyung Jo, Hamidreza Kasaei
Three-dimensional (3D) object recognition technology is being used as a core technology in advanced technologies such as autonomous driving of automobiles. There are two sets of ap…
Controllable Video Generation by Learning the Underlying Dynamical System with Neural ODE
Yucheng Xu, Li Nanbo, Arushi Goel +5
Videos depict the change of complex dynamical systems over time in the form of discrete image sequences. Generating controllable videos by learning the dynamical system is an impor…
3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks
Sudhakaran Jain, Hamidreza Kasaei
Service robots, in general, have to work independently and adapt to the dynamic changes happening in the environment in real-time. One important aspect in such scenarios is to cont…