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20212024
most citedEnhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models

2 citations · 10 across the 9 of their papers we have counts for

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cs.CV2024

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…

cs.CV2022★ 2 cited

Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models

Songsong Xiong, Georgios Tziafas, Hamidreza Kasaei

Robots operating in human-centered environments, such as retail stores, restaurants, and households, are often required to distinguish between similar objects in different contexts…

cs.CV2022★ 1 cited

Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition

Georgios Tziafas, Hamidreza Kasaei

The Vision Transformer (ViT) architecture has established its place in computer vision literature, however, training ViTs for RGB-D object recognition remains an understudied topic…

cs.CV2022★ 1 cited

Sim-To-Real Transfer of Visual Grounding for Human-Aided Ambiguity Resolution

Georgios Tziafas, Hamidreza Kasaei

Service robots should be able to interact naturally with non-expert human users, not only to help them in various tasks but also to receive guidance in order to resolve ambiguities…

cs.CV2021

Few-Shot Visual Grounding for Natural Human-Robot Interaction

Giorgos Tziafas, Hamidreza Kasaei

Natural Human-Robot Interaction (HRI) is one of the key components for service robots to be able to work in human-centric environments. In such dynamic environments, the robot need…