S
Sergiu Oprea
Researcher at University of Alicante
Publications - 29
Citations - 2203
Sergiu Oprea is an academic researcher from University of Alicante. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 8, co-authored 25 publications receiving 1399 citations.
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A Review on Deep Learning Techniques Applied to Semantic Segmentation.
Alberto Garcia-Garcia,Sergio Orts-Escolano,Sergiu Oprea,Victor Villena-Martinez,Jose Garcia-Rodriguez +4 more
TL;DR: A review on deep learning methods for semantic segmentation applied to various application areas as well as mandatory background concepts to help researchers decide which are the ones that best suit their needs and their targets.
Journal ArticleDOI
A survey on deep learning techniques for image and video semantic segmentation
Alberto Garcia-Garcia,Sergio Orts-Escolano,Sergiu Oprea,Victor Villena-Martinez,Pablo Martinez-Gonzalez,Jose Garcia-Rodriguez +5 more
TL;DR: A review on deep learning methods for semantic segmentation applied to various application areas and points out a set of promising future works to help researchers decide which are the ones that best suit their needs and goals.
Journal ArticleDOI
A Review on Deep Learning Techniques for Video Prediction
Sergiu Oprea,Pablo Martinez-Gonzalez,Alberto Garcia-Garcia,John Alejandro Castro-Vargas,Sergio Orts-Escolano,Jose Garcia-Rodriguez,Antonis A. Argyros +6 more
TL;DR: In this article, the authors provide a review on the deep learning methods for prediction in video sequences, as well as mandatory background concepts and the most used datasets, and carefully analyze existing video prediction models organized according to a proposed taxonomy.
Journal ArticleDOI
UnrealROX: an extremely photorealistic virtual reality environment for robotics simulations and synthetic data generation
Pablo Martinez-Gonzalez,Sergiu Oprea,Alberto Garcia-Garcia,Alvaro Jover-Alvarez,Sergio Orts-Escolano,Jose Garcia-Rodriguez +5 more
TL;DR: UnrealROX is an environment built over Unreal Engine 4 which aims to reduce that reality gap by leveraging hyperrealistic indoor scenes that are explored by robot agents which also interact with objects in a visually realistic manner in that simulated world.
Proceedings ArticleDOI
The RobotriX: An Extremely Photorealistic and Very-Large-Scale Indoor Dataset of Sequences with Robot Trajectories and Interactions
Alberto Garcia-Garcia,Pablo Martinez-Gonzalez,Sergiu Oprea,John Alejandro Castro-Vargas,Sergio Orts-Escolano,Jose Garcia-Rodriguez,Alvaro Jover-Alvarez +6 more
TL;DR: The RobotriX dataset as discussed by the authors is a large-scale dataset of indoor scenes with RGB-D and 3D annotations for a wide variety of robotic vision problems, including object tracking and object manipulation.