5 papers
HERB: Human-augmented Efficient Reinforcement learning for Bin-packing
Gojko Perovic, Nuno Ferreira Duarte, Atabak Dehban +3
Packing objects efficiently is a fundamental problem in logistics, warehouse automation, and robotics. When dealing with highly diverse 3D objects (household or grocery items), clo…
Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL
Manuel Serra Nunes, Atabak Dehban, Yiannis Demiris +1
Despite the significant advances in Deep Reinforcement Learning (RL) observed in the last decade, the amount of training experience necessary to learn effective policies remains on…
3DSGrasp: 3D Shape-Completion for Robotic Grasp
Seyed S. Mohammadi, Nuno F. Duarte, Dimitris Dimou +8
Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are…
CAD2DMD-SET: Synthetic Generation Tool of Digital Measurement Device CAD Model Datasets for fine-tuning Large Vision-Language Models
João Valente, Atabak Dehban, Rodrigo Ventura
Recent advancements in Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities across various multimodal tasks. They continue, however, to struggle with triv…
FLORA: Efficient Synthetic Data Generation for Object Detection in Low-Data Regimes via finetuning Flux LoRA
Alvaro Patricio, Atabak Dehban, Rodrigo Ventura
Recent advances in diffusion-based generative models have demonstrated significant potential in augmenting scarce datasets for object detection tasks. Nevertheless, most recent mod…