1.8k citations · 2.9k across the 66 of their papers we have counts for
85 papers
RoboVAD: A Large Cross-Domain Evaluation Benchmark for Anomaly Detection in Robotic Arm Manipulation Videos
Alexandru-Bogdan Dura, Sebastian Balmus, Radu Tudor Ionescu
Video anomaly detection (VAD) is an actively studied task, having wide applications in typical scenarios such as public surveillance and road traffic safety. The task is also relev…
Rip Current Segmentation: A Novel Benchmark and YOLOv8 Baseline Results
Andrei Dumitriu, Florin Tatui, Florin Miron +2
Rip currents are the leading cause of fatal accidents and injuries on many beaches worldwide, emphasizing the importance of automatically detecting these hazardous surface water cu…
An Open Hyperspectral Dataset with Sea-Land-Cloud Ground-Truth from the HYPSO-1 Satellite
Jon A. Justo, Joseph Garrett, Dennis D. Langer +3
Hyperspectral Imaging, employed in satellites for space remote sensing, like HYPSO-1, faces constraints due to few labeled data sets, affecting the training of AI models demanding…
Learning Using Generated Privileged Information by Text-to-Image Diffusion Models
Rafael-Edy Menadil, Mariana-Iuliana Georgescu, Radu Tudor Ionescu
Learning Using Privileged Information is a particular type of knowledge distillation where the teacher model benefits from an additional data representation during training, called…
RoDia: A New Dataset for Romanian Dialect Identification from Speech
Codrut Rotaru, Nicolae-Catalin Ristea, Radu Tudor Ionescu
We introduce RoDia, the first dataset for Romanian dialect identification from speech. The RoDia dataset includes a varied compilation of speech samples from five distinct regions…
JEDI: Joint Expert Distillation in a Semi-Supervised Multi-Dataset Student-Teacher Scenario for Video Action Recognition
Lucian Bicsi, Bogdan Alexe, Radu Tudor Ionescu +1
We propose JEDI, a multi-dataset semi-supervised learning method, which efficiently combines knowledge from multiple experts, learned on different datasets, to train and improve th…
CL-MAE: Curriculum-Learned Masked Autoencoders
Neelu Madan, Nicolae-Catalin Ristea, Kamal Nasrollahi +2
Masked image modeling has been demonstrated as a powerful pretext task for generating robust representations that can be effectively generalized across multiple downstream tasks. T…
Reverse Stable Diffusion: What prompt was used to generate this image?
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu +1
Text-to-image diffusion models have recently attracted the interest of many researchers, and inverting the diffusion process can play an important role in better understanding the…
Cascaded Cross-Modal Transformer for Request and Complaint Detection
Nicolae-Catalin Ristea, Radu Tudor Ionescu
We propose a novel cascaded cross-modal transformer (CCMT) that combines speech and text transcripts to detect customer requests and complaints in phone conversations. Our approach…
Class Anchor Margin Loss for Content-Based Image Retrieval
Alexandru Ghita, Radu Tudor Ionescu
The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by the chosen loss (objective) function. The majority of objective functions for neu…
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors
Nicolae-Catalin Ristea, Florinel-Alin Croitoru, Radu Tudor Ionescu +3
We propose an efficient abnormal event detection model based on a lightweight masked auto-encoder (AE) applied at the video frame level. The novelty of the proposed model is threef…
iQPP: A Benchmark for Image Query Performance Prediction
Eduard Poesina, Radu Tudor Ionescu, Josiane Mothe
To date, query performance prediction (QPP) in the context of content-based image retrieval remains a largely unexplored task, especially in the query-by-example scenario, where th…
FreCDo: A Large Corpus for French Cross-Domain Dialect Identification
Mihaela Gaman, Adrian-Gabriel Chifu, William Domingues +1
We present a novel corpus for French dialect identification comprising 413,522 French text samples collected from public news websites in Belgium, Canada, France and Switzerland. T…
Audiovisual Masked Autoencoders
Mariana-Iuliana Georgescu, Eduardo Fonseca, Radu Tudor Ionescu +3
Can we leverage the audiovisual information already present in video to improve self-supervised representation learning? To answer this question, we study various pretraining archi…
Lightning Fast Video Anomaly Detection via Adversarial Knowledge Distillation
Florinel-Alin Croitoru, Nicolae-Catalin Ristea, Dana Dascalescu +3
We propose a very fast frame-level model for anomaly detection in video, which learns to detect anomalies by distilling knowledge from multiple highly accurate object-level teacher…
Diversity-Promoting Ensemble for Medical Image Segmentation
Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron
Medical image segmentation is an actively studied task in medical imaging, where the precision of the annotations is of utter importance towards accurate diagnosis and treatment. I…
Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection
Neelu Madan, Nicolae-Catalin Ristea, Radu Tudor Ionescu +4
Anomaly detection has recently gained increasing attention in the field of computer vision, likely due to its broad set of applications ranging from product fault detection on indu…
Diffusion Models in Vision: A Survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu +1
Denoising diffusion models represent a recent emerging topic in computer vision, demonstrating remarkable results in the area of generative modeling. A diffusion model is a deep ge…
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
Antonio Barbalau, Radu Tudor Ionescu, Mariana-Iuliana Georgescu +6
A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature. Due to its highly accurate results, the method attracted…
VeriDark: A Large-Scale Benchmark for Authorship Verification on the Dark Web
Andrei Manolache, Florin Brad, Antonio Barbalau +2
The DarkWeb represents a hotbed for illicit activity, where users communicate on different market forums in order to exchange goods and services. Law enforcement agencies benefit f…
Learning Rate Curriculum
Florinel-Alin Croitoru, Nicolae-Catalin Ristea, Radu Tudor Ionescu +1
Most curriculum learning methods require an approach to sort the data samples by difficulty, which is often cumbersome to perform. In this work, we propose a novel curriculum learn…
Multimodal Multi-Head Convolutional Attention with Various Kernel Sizes for Medical Image Super-Resolution
Mariana-Iuliana Georgescu, Radu Tudor Ionescu, Andreea-Iuliana Miron +4
Super-resolving medical images can help physicians in providing more accurate diagnostics. In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniqu…
SepTr: Separable Transformer for Audio Spectrogram Processing
Nicolae-Catalin Ristea, Radu Tudor Ionescu, Fahad Shahbaz Khan
Following the successful application of vision transformers in multiple computer vision tasks, these models have drawn the attention of the signal processing community. This is bec…
Discriminability-enforcing loss to improve representation learning
Florinel-Alin Croitoru, Diana-Nicoleta Grigore, Radu Tudor Ionescu
During the training process, deep neural networks implicitly learn to represent the input data samples through a hierarchy of features, where the size of the hierarchy is determine…