Learning to adapt for stereo by Tonioni, A, Rahnama, O, Joy, T, Di Stefano, L, Ajanthan, T, Torr, PHS

“…Real world applications of stereo depth estimation require models that are robust to dynamic variations in the environment. …”

Domain-invariant stereo matching networks by Zhang, F, Qi, X, Yang, R, Prisacariu, V, Wah, B, Torr, PHS

“…In this paper, we aim at designing a domain-invariant stereo matching network (DSMNet) that generalizes well to unseen scenes. …”

Joint optimization for object class segmentation and dense stereo reconstruction by Ladický, L, Sturgess, P, Russell, C, Sengupta, S, Bastanlar, Y, Clocksin, W, Torr, PHS

“…The problems of dense stereo reconstruction and object class segmentation can both be formulated as Random Field labeling problems, in which every pixel in the image is assigned a label corresponding to either its disparity, or an object class such as road or building. …”

Multiview stereo via volumetric graph-cuts and occlusion robust photo-consistency by Vogiatzis, G, Hernández Esteban, C, Torr, PHS, Cipolla, R

“…This paper presents a volumetric formulation for the multiview stereo problem which is amenable to a computationally tractable global optimization using Graph-cuts. …”

Efficient dense stereo with occlusions for new view-synthesis by four-state dynamic programming by Criminisi, A, Blake, A, Rother, C, Shotton, J, Torr, PHS

“…The new technique is based on an improved, dynamic-programming, stereo algorithm for efficient novel view generation. …”

Filter-based mean-field inference for random fields with higher-order terms and product label-spaces by Vineet, V, Warrell, J, Torr, PHS

“…We demonstrate our techniques on joint stereo and object labeling problems, as well as object class segmentation, showing in addition for joint object-stereo labeling how our method provides an efficient approach to inference in product label-spaces. …”

Filter-based mean-field inference for random fields with higher-order terms and product label-spaces by Vineet, V, Warrell, J, Torr, PHS

“…We demonstrate our techniques on joint stereo and object labelling problems, as well as object class segmentation, showing in addition for joint object-stereo labelling how our method provides an efficient approach to inference in product label-spaces. …”

Reconstructing relief surfaces by Vogiatzis, G, Torr, PHS, Seitz, SM, Cipolla, R

“…This paper generalizes Markov Random Field (MRF) stereo methods to the generation of surface relief (height) fields rather than disparity or depth maps. …”

Incremental dense multi-modal 3D scene reconstruction by Miksik, O, Amar, Y, Vineet, V, Pérez, P, Torr, PHS

“…Often, we use a combination of a stereo camera and lidar, however, process the acquired data in independent pipelines which generally leads to sub-optimal performance since both sensors suffer from different drawbacks. …”

A tiered move-making algorithm for general pairwise MRFs by Vineet, V, Warrell, J, Torr, PHS

“…We evaluate the algorithm on many benchmark labeling problems such as stereo, image segmentation, image stitching and image denoising, as well as random energy minimization. …”

Dynamic hybrid algorithms for MAP inference in discrete MRFs by Alahari, K, Kohli, P, Torr, PHS

“…We test the performance of our methods on energy functions encountered in the problems of stereo matching and color and object-based segmentation. …”

Efficient relaxations for dense CRFs with sparse higher-order potentials by Joy, T, Desmaison, A, Ajanthan, T, Bunel, R, Salzmann, M, Kohli, P, Torr, PHS, Kumar, MP

“…<p>Dense conditional random fields (CRFs) have become a popular framework for modelling several problems in computer vision such as stereo correspondence and multi-class semantic segmentation. …”