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- Gian Luca ForestiSuggested from co-authorship
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Works209 from public data
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- The Eighth Visual Object Tracking VOT2020 Challenge Results350
A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in theVDT challenges.
- Wide-Slice Residual Networks for Food Recognition228
This work introduces a new deep scheme that is designed to handle the food structure, and first introduces a slice convolution block to capture the vertical food traits that are common to a large number of categories.
- NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results191
The NTIRE 2020 challenge addresses the real world setting, where paired true high and low-resolution images are unavailable, and the ultimate goal is to achieve the best perceptual quality, evaluated using a human study.
- Saliency Weighted Features for Person Re-identification144
This work proposes a novel person re-identification approach, inspired by human gazing capabilities, that uses the salient regions of a given person as a weighting tool in the image feature extraction process and is compared with best state-of-the-art approaches to show its overall superior performance.
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- The Ninth Visual Object Tracking VOT2021 Challenge Results127
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative; results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years.
- Temporal Model Adaptation for Person Re-identification123
This work introduces a similarity-dissimilarity learning method which can be trained in an incremental fashion by means of a stochastic alternating directions methods of multipliers optimization procedure and exploits a graph-based approach to present the user only the most informative probe-gallery matches that should be used to update the model.
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- AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results101
The AIM 2020 challenge on efficient single image super-resolution was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images with focus on the proposed solutions and results.
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- NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results83
This paper reviews the NTIRE 2024 challenge on image super-resolution (×4), highlighting the solutions proposed and the outcomes obtained, and offers a comprehensive overview of current trends in this field.
- A network of co-operative cameras for visual surveillance80
A network of co-operative cameras for the visual surveillance of parking lots employs multiple subnets able to manage static and active cameras in a hierarchical framework and is able to track multiple targets simultaneously and in real-time throughout the controlled areas.
- Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images79
This study proposes a new deep learning method to track, accurately and efficiently, the femoral condyle cartilage in ultrasound sequences, which were acquired under several clinical conditions, mimicking realistic surgical setups.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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