activity
20162023
most citedAutomatic Hierarchical Classification of Kelps using Deep Residual Features

62 citations · 208 across the 18 of their papers we have counts for

collaborators

20 papers

cs.CV2023

A Multi-modal Garden Dataset and Hybrid 3D Dense Reconstruction Framework Based on Panoramic Stereo Images for a Trimming Robot

Can Pu, Chuanyu Yang, Jinnian Pu +2

Recovering an outdoor environment's surface mesh is vital for an agricultural robot during task planning and remote visualization. Our proposed solution is based on a newly-designe…

cs.RO2023

A General Mobile Manipulator Automation Framework for Flexible Manufacturing in Hostile Industrial Environments

Can Pu, Chuanyu Yang, Jinnian Pu +1

To enable a mobile manipulator to perform human tasks from a single teaching demonstration is vital to flexible manufacturing. We call our proposed method MMPA (Mobile Manipulator…

cs.CV2021★ 19 cited

Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views

Li Nanbo, Cian Eastwood, Robert B. Fisher

Learning object-centric representations of multi-object scenes is a promising approach towards machine intelligence, facilitating high-level reasoning and control from visual senso…

cs.CV2020★ 19 cited

RGB-D-based Framework to Acquire, Visualize and Measure the Human Body for Dietetic Treatments

Andrés Fuster-Guilló, Jorge Azorín-López, Marcelo Saval-Calvo +3

This research aims to improve dietetic-nutritional treatment using state-of-the-art RGB-D sensors and virtual reality (VR) technology. Recent studies show that adherence to treatme…

cs.CV2020★ 35 cited

When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)

Victor Villena-Martinez, Sergiu Oprea, Marcelo Saval-Calvo +3

Registration is the process that computes the transformation that aligns sets of data. Commonly, a registration process can be divided into four main steps: target selection, featu…

cs.LG2020★ 2 cited

Incremental Unsupervised Domain-Adversarial Training of Neural Networks

Antonio-Javier Gallego, Jorge Calvo-Zaragoza, Robert B. Fisher

In the context of supervised statistical learning, it is typically assumed that the training set comes from the same distribution that draws the test samples. When this is not the…

cs.CV2019★ 62 cited

Automatic Hierarchical Classification of Kelps using Deep Residual Features

Ammar Mahmood, Ana Giraldo Ospina, Mohammed Bennamoun +6

Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal…

cs.CV2019★ 1 cited

UDFNet: Unsupervised Disparity Fusion with Adversarial Networks

Can Pu, Robert B. Fisher

Existing disparity fusion methods based on deep learning achieve state-of-the-art performance, but they require ground truth disparity data to train. As far as I know, this is the…

cs.RO2018★ 20 cited

TrimBot2020: an outdoor robot for automatic gardening

Nicola Strisciuglio, Radim Tylecek, Michael Blaich +9

Robots are increasingly present in modern industry and also in everyday life. Their applications range from health-related situations, for assistance to elderly people or in surgic…

cs.CV2018★ 1 cited

DUGMA: Dynamic Uncertainty-Based Gaussian Mixture Alignment

Can Pu, Nanbo Li, Radim Tylecek +1

Registering accurately point clouds from a cheap low-resolution sensor is a challenging task. Existing rigid registration methods failed to use the physical 3D uncertainty distribu…

cs.CV2018★ 14 cited

Sdf-GAN: Semi-supervised Depth Fusion with Multi-scale Adversarial Networks

Can Pu, Runzi Song, Radim Tylecek +2

Refining raw disparity maps from different algorithms to exploit their complementary advantages is still challenging. Uncertainty estimation and complex disparity relationships amo…

cs.CV2018

Hybrid Multi-camera Visual Servoing to Moving Target

Hanz Cuevas-Velasquez, Nanbo Li, Radim Tylecek +2

Visual servoing is a well-known task in robotics. However, there are still challenges when multiple visual sources are combined to accurately guide the robot or occlusions appear.…

cs.CV2018★ 27 cited

3D non-rigid registration using color: Color Coherent Point Drift

Marcelo Saval-Calvo, Jorge Azorin-Lopez, Andres Fuster-Guillo +2

Research into object deformations using computer vision techniques has been under intense study in recent years. A widely used technique is 3D non-rigid registration to estimate th…

cs.CV2017

Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction

Jie Zhang, Christos Maniatis, Luis Horna +1

The availability of high-speed 3D video sensors has greatly facilitated 3D shape acquisition of dynamic and deformable objects, but high frame rate 3D reconstruction is always degr…

cs.CV2017★ 2 cited

Best Viewpoint Tracking for Camera Mounted on Robotic Arm with Dynamic Obstacles

Christos Maniatis, Marcelo Saval-Calvo, Radim Tylecek +1

The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but w…

cs.CV2017★ 1 cited

Robust Rigid Point Registration based on Convolution of Adaptive Gaussian Mixture Models

Can Pu, Nanbo Li, Robert B Fisher

Matching 3D rigid point clouds in complex environments robustly and accurately is still a core technique used in many applications. This paper proposes a new architecture combining…

cs.CV2016★ 1 cited

Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches

Erik Rodner, Marcel Simon, Robert B. Fisher +1

In this paper, we study the sensitivity of CNN outputs with respect to image transformations and noise in the area of fine-grained recognition. In particular, we answer the followi…

cs.CV2016★ 1 cited

Recoding Color Transfer as a Color Homography

Han Gong, Graham D. Finlayson, Robert B. Fisher

Color transfer is an image editing process that adjusts the colors of a picture to match a target picture's color theme. A natural color transfer not only matches the color styles…

cs.CV2016

Color Homography Color Correction

Graham D. Finlayson, Han Gong, Robert B. Fisher

Homographies -- a mathematical formalism for relating image points across different camera viewpoints -- are at the foundations of geometric methods in computer vision and are used…

cs.CV2016★ 3 cited

Color Homography

Graham D. Finlayson, Han Gong, Robert B. Fisher

We show the surprising result that colors across a change in viewing condition (changing light color, shading and camera) are related by a homography. Our homography color correcti…