47 citations · 148 across the 20 of their papers we have counts for
20 papers
FineVAU: A Novel Human-Aligned Benchmark for Fine-Grained Video Anomaly Understanding
João Pereira, Vasco Lopes, João Neves +1
Video Anomaly Understanding (VAU) is a novel task focused on describing unusual occurrences in videos. Despite growing interest, the evaluation of VAU remains an open challenge. Ex…
Chain-of-Anomaly Thoughts with Large Vision-Language Models
Pedro Domingos, João Pereira, Vasco Lopes +2
Automated video surveillance with Large Vision-Language Models is limited by their inherent bias towards normality, often failing to detect crimes. While Chain-of-Thought reasoning…
Seeing Across Time and Views: Multi-Temporal Cross-View Learning for Robust Video Person Re-Identification
Md Rashidunnabi, Kailash A. Hambarde, Vasco Lopes +2
Video-based person re-identification (ReID) in cross-view domains (for example, aerial-ground surveillance) remains an open problem because of extreme viewpoint shifts, scale dispa…
Self-ReS: Self-Reflection in Large Vision-Language Models for Long Video Understanding
Joao Pereira, Vasco Lopes, David Semedo +1
Large Vision-Language Models (LVLMs) demonstrate remarkable performance in short-video tasks such as video question answering, but struggle in long-video understanding. The linear…
Zero-Shot Action Recognition in Surveillance Videos
Joao Pereira, Vasco Lopes, David Semedo +1
The growing demand for surveillance in public spaces presents significant challenges due to the shortage of human resources. Current AI-based video surveillance systems heavily rel…
Are Neural Architecture Search Benchmarks Well Designed? A Deeper Look Into Operation Importance
Vasco Lopes, Bruno Degardin, Luís A. Alexandre
Neural Architecture Search (NAS) benchmarks significantly improved the capability of developing and comparing NAS methods while at the same time drastically reduced the computation…
Guided Evolutionary Neural Architecture Search With Efficient Performance Estimation
Vasco Lopes, Miguel Santos, Bruno Degardin +1
Neural Architecture Search (NAS) methods have been successfully applied to image tasks with excellent results. However, NAS methods are often complex and tend to converge to local…
Towards Less Constrained Macro-Neural Architecture Search
Vasco Lopes, Luís A. Alexandre
Networks found with Neural Architecture Search (NAS) achieve state-of-the-art performance in a variety of tasks, out-performing human-designed networks. However, most NAS methods h…
Guided Evolution for Neural Architecture Search
Vasco Lopes, Miguel Santos, Bruno Degardin +1
Neural Architecture Search (NAS) methods have been successfully applied to image tasks with excellent results. However, NAS methods are often complex and tend to converge to local…
Generative Adversarial Graph Convolutional Networks for Human Action Synthesis
Bruno Degardin, João Neves, Vasco Lopes +3
Synthesising the spatial and temporal dynamics of the human body skeleton remains a challenging task, not only in terms of the quality of the generated shapes, but also of their di…
REGINA - Reasoning Graph Convolutional Networks in Human Action Recognition
Bruno Degardin, Vasco Lopes, Hugo Proença
It is known that the kinematics of the human body skeleton reveals valuable information in action recognition. Recently, modeling skeletons as spatio-temporal graphs with Graph Con…
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search
Vasco Lopes, Saeid Alirezazadeh, Luís A. Alexandre
Neural Architecture Search (NAS) has shown excellent results in designing architectures for computer vision problems. NAS alleviates the need for human-defined settings by automati…
An AutoML-based Approach to Multimodal Image Sentiment Analysis
Vasco Lopes, António Gaspar, Luís A. Alexandre +1
Sentiment analysis is a research topic focused on analysing data to extract information related to the sentiment that it causes. Applications of sentiment analysis are wide, rangin…
Auto-Classifier: A Robust Defect Detector Based on an AutoML Head
Vasco Lopes, Luís A. Alexandre
The dominant approach for surface defect detection is the use of hand-crafted feature-based methods. However, this falls short when conditions vary that affect extracted images. So…
HMCNAS: Neural Architecture Search using Hidden Markov Chains and Bayesian Optimization
Vasco Lopes, Luís A. Alexandre
Neural Architecture Search has achieved state-of-the-art performance in a variety of tasks, out-performing human-designed networks. However, many assumptions, that require human de…
A Hybrid Method for Training Convolutional Neural Networks
Vasco Lopes, Paulo Fazendeiro
Artificial Intelligence algorithms have been steadily increasing in popularity and usage. Deep Learning, allows neural networks to be trained using huge datasets and also removes t…
GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection
João C. Neves, Ruben Tolosana, Ruben Vera-Rodriguez +3
The availability of large-scale facial databases, together with the remarkable progresses of deep learning technologies, in particular Generative Adversarial Networks (GANs), have…
MANAS: Multi-Agent Neural Architecture Search
Vasco Lopes, Fabio Maria Carlucci, Pedro M Esperança +6
The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a g…
Controlling Robots using Artificial Intelligence and a Consortium Blockchain
Vasco Lopes, Luís A. Alexandre, Nuno Pereira
Blockchain is a disruptive technology that is normally used within financial applications, however it can be very beneficial also in certain robotic contexts, such as when an immut…
An Overview of Blockchain Integration with Robotics and Artificial Intelligence
Vasco Lopes, Luís A. Alexandre
Blockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a re…