activity
20162021
most citedHow hard can it be? Estimating the difficulty of visual search in an image

6 citations · 10 across the 8 of their papers we have counts for

collaborators

22 papers

cs.CV2021

TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval

Ioana Croitoru, Simion-Vlad Bogolin, Marius Leordeanu +4

In recent years, considerable progress on the task of text-video retrieval has been achieved by leveraging large-scale pretraining on visual and audio datasets to construct powerfu…

cs.LG2021

Self-Supervised Learning in Multi-Task Graphs through Iterative Consensus Shift

Emanuela Haller, Elena Burceanu, Marius Leordeanu

The human ability to synchronize the feedback from all their senses inspired recent works in multi-task and multi-modal learning. While these works rely on expensive supervision, o…

cs.CV2020

Iterative Knowledge Exchange Between Deep Learning and Space-Time Spectral Clustering for Unsupervised Segmentation in Videos

Emanuela Haller, Adina Magda Florea, Marius Leordeanu

We propose a dual system for unsupervised object segmentation in video, which brings together two modules with complementary properties: a space-time graph that discovers objects i…

cs.CV2020

Semantics through Time: Semi-supervised Segmentation of Aerial Videos with Iterative Label Propagation

Alina Marcu, Vlad Licaret, Dragos Costea +1

Semantic segmentation is a crucial task for robot navigation and safety. However, current supervised methods require a large amount of pixelwise annotations to yield accurate resul…

cs.CV2020

Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph Consensus

Marius Leordeanu, Mihai Pirvu, Dragos Costea +3

We address the challenging problem of semi-supervised learning in the context of multiple visual interpretations of the world by finding consensus in a graph of neural networks. Ea…

cs.CV2020

In Search of Life: Learning from Synthetic Data to Detect Vital Signs in Videos

Florin Condrea, Victor-Andrei Ivan, Marius Leordeanu

Automatically detecting vital signs in videos, such as the estimation of heart and respiration rates, is a challenging research problem in computer vision with important applicatio…