Search Results for author:
Found 25 papers, 5 papers with code
Global Point Cloud Registration Network for Large Transformations
In this paper, we present ReLaTo (Registration for Large Transformations), an architecture that faces the cases where large transformations happen while maintaining good performance for local transformations.
DexDLO: Learning Goal-Conditioned Dexterous Policy for Dynamic Manipulation of Deformable Linear Objects
We present DexDLO, a model-free framework that learns dexterous dynamic manipulation policies for deformable linear objects with a fixed-base dexterous hand in an end-to-end way.
Monitoring Inactivity of Single Older Adults at Home
A new application for real-time monitoring of the lack of movement in older adults' own homes is proposed, aiming to support people's lives and independence in their later years.
A Multi-modal Garden Dataset and Hybrid 3D Dense Reconstruction Framework Based on Panoramic Stereo Images for a Trimming Robot
Next, the refined disparity maps are converted into full-view point clouds or single-view point clouds for the pose fusion module.
A General Mobile Manipulator Automation Framework for Flexible Manufacturing in Hostile Industrial Environments
More specifically, in the automation stage, the robot navigates to the specified location without the need of a precise parking.
3D Lip Event Detection via Interframe Motion Divergence at Multiple Temporal Resolutions
We define a motion divergence measure using 3D lip landmarks to quantify the interframe dynamics of a 3D speaking lip.
Learning Object-Centric Representations of Multi-Object Scenes from Multiple Views
In order to sidestep the main technical difficulty of the multi-object-multi-view scenario -- maintaining object correspondences across views -- MulMON iteratively updates the latent object representations for a scene over multiple views.
Object-Centric Representation Learning with Generative Spatial-Temporal Factorization
We train DyMON on multi-view-dynamic-scene data and show that DyMON learns -- without supervision -- to factorize the entangled effects of observer motions and scene object dynamics from a sequence of observations, and constructs scene object spatial representations suitable for rendering at arbitrary times (querying across time) and from arbitrary viewpoints (querying across space).
Two Heads are Better than One: Geometric-Latent Attention for Point Cloud Classification and Segmentation
We present an innovative two-headed attention layer that combines geometric and latent features to segment a 3D scene into semantically meaningful subsets.
RGB-D-based Framework to Acquire, Visualize and Measure the Human Body for Dietetic Treatments
The 3D body models will be used for studying the effect of visualization on adherence to obesity treatment using 2D and VR devices.
When Deep Learning Meets Data Alignment: A Review on Deep Registration Networks (DRNs)
Recent advancements in machine learning could be a turning point in these issues, particularly with the development of deep learning (DL) techniques, which are helping to improve multiple computer vision problems through an abstract understanding of the input data.
Incremental Unsupervised Domain-Adversarial Training of Neural Networks
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.
Automatic Hierarchical Classification of Kelps using Deep Residual Features
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 seas.
UDFNet: Unsupervised Disparity Fusion with Adversarial Networks
In this paper, a mathematical model for disparity fusion is proposed to guide an adversarial network to train effectively without ground truth disparity data.
Sdf-GAN: Semi-supervised Depth Fusion with Multi-scale Adversarial Networks
into a refiner network to better refine raw disparity inputs.
DUGMA: Dynamic Uncertainty-Based Gaussian Mixture Alignment
Existing rigid registration methods failed to use the physical 3D uncertainty distribution of each point from a real sensor in the dynamic alignment process mainly because the uncertainty model for a point is static and invariant and it is hard to describe the change of these physical uncertainty models in the registration process.
Hybrid Multi-camera Visual Servoing to Moving Target
A Master supervisor task selects between using the EtoH or the EinH, depending on the distance between the robot and target.
3D non-rigid registration using color: Color Coherent Point Drift
Evaluation is performed using synthetic and real data.
Intensity Video Guided 4D Fusion for Improved Highly Dynamic 3D Reconstruction
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 degraded by spatial noise and temporal fluctuations.
Best Viewpoint Tracking for Camera Mounted on Robotic Arm with Dynamic Obstacles
The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade.
Robust Rigid Point Registration based on Convolution of Adaptive Gaussian Mixture Models
Matching 3D rigid point clouds in complex environments robustly and accurately is still a core technique used in many applications.
Fine-grained Recognition in the Noisy Wild: Sensitivity Analysis of Convolutional Neural Networks Approaches
In this paper, we study the sensitivity of CNN outputs with respect to image transformations and noise in the area of fine-grained recognition.
Recoding Color Transfer as a Color Homography
A powerful form of shading adjustment is shown to be a global shading curve by which the same shading homography can be applied elsewhere.
Color Homography Color Correction
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 in geometric camera calibration, image registration, and stereo vision and other tasks.
Color Homography
We show the surprising result that colors across a change in viewing condition (changing light color, shading and camera) are related by a homography.
