69 citations · 107 across the 6 of their papers we have counts for
8 papers
3D Scene Geometry Estimation from 360 Imagery: A Survey
Thiago Lopes Trugillo da Silveira, Paulo Gamarra Lessa Pinto, Jeffri Erwin Murrugarra Llerena +1
This paper provides a comprehensive survey on pioneer and state-of-the-art 3D scene geometry estimation methodologies based on single, two, or multiple images captured under the om…
SVBR-NET: A Non-Blind Spatially Varying Defocus Blur Removal Network
Ali Karaali, Claudio Rosito Jung
Defocus blur is a physical consequence of the optical sensors used in most cameras. Although it can be used as a photographic style, it is commonly viewed as an image degradation m…
Gaussian Bounding Boxes and Probabilistic Intersection-over-Union for Object Detection
Jeffri M. Llerena, Luis Felipe Zeni, Lucas N. Kristen +1
Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a fuzzy representation of object regions using Gaus…
Improving the Classification of Rare Chords with Unlabeled Data
Marcelo Bortolozzo, Rodrigo Schramm, Claudio R. Jung
In this work, we explore techniques to improve performance for rare classes in the task of Automatic Chord Recognition (ACR). We first explored the use of the focal loss in the con…
Deep Multi-Scale Feature Learning for Defocus Blur Estimation
Ali Karaali, Naomi Harte, Claudio Rosito Jung
This paper presents an edge-based defocus blur estimation method from a single defocused image. We first distinguish edges that lie at depth discontinuities (called depth edges, fo…
Distilling Knowledge from Refinement in Multiple Instance Detection Networks
Luis Felipe Zeni, Claudio Jung
Weakly supervised object detection (WSOD) aims to tackle the object detection problem using only labeled image categories as supervision. A common approach used in WSOD to deal wit…
Superpixel Image Classification with Graph Attention Networks
Pedro H. C. Avelar, Anderson R. Tavares, Thiago L. T. da Silveira +2
This paper presents a methodology for image classification using Graph Neural Network (GNN) models. We transform the input images into region adjacency graphs (RAGs), in which regi…
Collective behavior recognition using compact descriptors
Gustavo Fuhr, Claudio Rosito Jung
This paper presents a novel hierarchical approach for collective behavior recognition based solely on ground-plane trajectories. In the first layer of our classifier, we introduce…