34 citations · 36 across the 7 of their papers we have counts for
9 papers
AHMAD: Adaptive Hybrid Multi-task Vision Learning with Assisted Distillation for Keypoint Detection
Mohammad Mahdi, Nedyalko Prisadnikov, Yuqian Fu +3
Generalist multitasking vision models aim to unify multiple vision tasks within a single framework, enabling more efficient and versatile learning. However, handling diverse vision…
Accelerated Decoding of Centroid Positional Encoding for Instance Segmentation
Carmelo Scribano, Filippo Muzzini, Nedyalko Prisadnikov +6
Beyond model inference, the decoding stage, which converts raw network outputs into task-level representations, constitutes a significant portion of the execution cost. Despite its…
Accelerating Vision Foundation Models with Drop-in Depthwise Convolution
Carmelo Scribano, Mohammad Mahdi, Nedyalko Prisadnikov +5
Pretrained vision foundation models deliver strong performance across tasks with limited fine-tuning. However, their Vision Transformer (ViT) backbones impose high inference costs,…
Low-Latency Embedded Driver Monitoring System with a Multi-Task Neural Network
Carmelo Scribano, Giovanni Cappelletti, Elia Giacobazzi +3
Road traffic accidents remain a significant global concern, with the majority attributed to human factors such as driver distraction and fatigue. This study proposes a camera-based…
Segment Anything for Satellite Imagery: A Strong Baseline and a Regional Dataset for Automatic Field Delineation
Carmelo Scribano, Elena Govi, Paolo Bertellini +3
Accurate mapping of agricultural field boundaries is essential for the efficient operation of agriculture. Automatic extraction from high-resolution satellite imagery, supported by…
Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation
Elena Govi, Davide Sapienza, Carmelo Scribano +5
In recent years, there has been a growing trend of using data-driven methods in industrial settings. These kinds of methods often process video images or parts, therefore the integ…
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning
Carmelo Scribano, Giorgia Franchini, Ignacio Sañudo Olmedo +1
Perceiving the surrounding environment is essential for enabling autonomous or assisted driving functionalities. Common tasks in this domain include detecting road users, as well a…
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform
Carmelo Scribano, Giorgia Franchini, Marco Prato +1
Since their introduction the Trasformer architectures emerged as the dominating architectures for both natural language processing and, more recently, computer vision applications.…
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
Carmelo Scribano, Davide Sapienza, Giorgia Franchini +2
Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence. The AI City Challenge Track 5 for Natural Language-Ba…