CVPR

Metric Learning for Image Registration

Image registration is a key technique in medical image analysis to estimate deformations between image pairs. A good deformation model is important for high-quality estimates. However, most existing approaches use ad-hoc deformation models chosen for …

Networks for Joint Affine and Non-Parametric Image Registration

We introduce an end-to-end deep-learning framework for 3D medical image registration. In contrast to existing approaches, our framework combines two registration methods: an affine registration and a vector momentum-parameterized stationary velocity …

AGA: Attribute-Guided Augmentation

We consider the problem of data augmentation, ie, generating artificial samples to extend a given corpus of training data. Specifically, we propose attributed-guided augmentation (AGA) which learns a mapping that allows to synthesize data such that …

One-Shot Learning of Scene Locations via Feature Trajectory Transfer

The appearance of (outdoor) scenes changes considerably with the strength of certain transient attributes, such as" rainy"," dark" or" sunny". Obviously, this also affects the representation of an image in feature space, eg, as activations at a …

Registration of Developmental Image Sequences with Missing Data

Longitudinal image registration is commonly used to establish spatial correspondence between images when investigating temporal changes in brain morphology. Most image registration methods have been developed to align images that are similar in …

Scene Parsing with Object Instances and Occlusion Ordering

This work proposes a method to interpret a scene by assigning a semantic label at every pixel and inferring the spatial extent of individual object instances together with their occlusion relationships. Starting with an initial pixel labeling and a …

An optimal control approach for deformable registration

This paper addresses large-displacement-diffeomorphic mapping registration from an optimal control perspective. This viewpoint leads to two complementary formulations. One approach requires the explicit computation of coordinate maps, whereas the …

Continuous maximal flows and Wulff shapes: Application to MRFs

Convex and continuous energy formulations for low level vision problems enable efficient search procedures for the corresponding globally optimal solutions. In this work we extend the well-established continuous, isotropic capacity-based maximal flow …

Dynamic Geodesic Snakes for Visual Tracking

Visual tracking using active contours is usually accomplished in a static framework. The active contour tracks the object of interest in a given frame of an image sequence, and then a subsequent prediction step ensures good initial placement for the …