Publications

Export 185 results:
Author Title [ Type(Desc)] Year
Filters: Author is Carsten Rother  [Clear All Filters]
Conference Paper
Sellen, A, Fogg, A, Aitken, M, Hodges, S, Rother, C and Wood, K (2007). Do life-logging technologies support memory for the past? An experimental study using sensecam. Conference on Human Factors in Computing Systems - Proceedings. 81–90
Brachmann, E, Krull, A, Nowozin, S, Shotton, J, Michel, F, Gumhold, S and Rother, C (2017). DSAC - Differentiable RANSAC for camera localization. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 2492–2500. http://arxiv.org/abs/1611.05705
Brachmann, E and Rother, C (2019). Expert sample consensus applied to camera re-localization. Proceedings of the IEEE International Conference on Computer Vision. 2019-Octob 7524–7533. http://arxiv.org/abs/1908.02484
Bleyer, M, Rhemann, C and Rother, C (2012). Extracting 3D scene-consistent object proposals and depth from stereo images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7576 LNCS 467–481. http://vision.middlebury.edu/stereo/
Bleyer, M, Rhemann, C and Rother, C (2012). Extracting 3D scene-consistent object proposals and depth from stereo images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7576 LNCS 467–481
Torresani, L, Kolmogorov, V and Rother, C (2008). Feature correspondence via graph matching: Models and global optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5303 LNCS 596–609
Torresani, L, Kolmogorov, V and Rother, C (2008). Feature correspondence via graph matching: Models and global optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5303 LNCS 596–609
Lempitsky, V, Roth, S and Rother, C (2008). FusionFlow: Discrete-continuous optimization for optical flow estimation. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Gulshan, V, Rother, C, Criminisi, A, Blake, A and Zisserman, A (2010). Geodesic star convexity for interactive image segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 3129–3136
Abu Alhaija, H, Mustikovela, S Karthik, Geiger, A and Rother, C (2019). Geometric Image Synthesis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11366 LNCS 85–100. https://youtu.be/W2tFCz9xJoU
Michel, F, Kirillov, A, Brachmann, E, Krull, A, Gumhold, S, Savchynskyy, B and Rother, C (2017). Global hypothesis generation for 6D object pose estimation. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 115–124. http://arxiv.org/abs/1612.02287
He, K, Rhemann, C, Rother, C, Tang, X and Sun, J (2011). A global sampling method for alpha matting. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2049–2056
Rother, C, Kolmogorov, V and Blake, A (2004). "GrabCut" - Interactive foreground extraction using iterated graph cuts. ACM Transactions on Graphics. 23 309–314
Vicente, S, Kolmogorov, V and Rother, C (2008). Graph cut based image segmentation with connectivity priors. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Abu Alhaija, H, Sellent, A, Kondermann, D and Rother, C (2015). Graphflow—6D large displacement scene flow via graph matching. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9358 285–296
Rhemann, C, Rother, C, Rav-Acha, A and Sharp, T (2008). High resolution matting via interactive trimap segmentation. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Rhemann, C, Rother, C, Rav-Acha, A and Sharp, T (2008). High resolution matting via interactive trimap segmentation. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Rhemann, C, Rother, C, Rav-Acha, A and Sharp, T (2008). High resolution matting via interactive trimap segmentation. 26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
Vineet, V, Rother, C and Torr, P H S (2013). Higher order priors for joint intrinsic image, objects, and attributes estimation. Advances in Neural Information Processing Systems
Hornáček, M, Besse, F, Kautz, J, Fitzgibbon, A and Rother, C (2014). Highly overparameterized optical flow using PatchMatch belief propagation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8691 LNCS 220–234
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
Lempitsky, V, Blake, A and Rother, C (2008). Image segmentation by branch-and-mincut. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5305 LNCS 15–29
Lempitsky, V, Kohli, P, Rother, C and Sharp, T (2009). Image segmentation with a bounding box prior. Proceedings of the IEEE International Conference on Computer Vision. 277–284
Töppe, E, Oswald, M R, Cremers, D and Rother, C (2011). Image-based 3D modeling via cheeger sets. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6492 LNCS 53–64
Rhemann, C, Rother, C and Gelautz, M (2008). Improving color modeling for alpha matting. BMVC 2008 - Proceedings of the British Machine Vision Conference 2008
Kirillov, A, Savchynskyy, B, Schlesinger, D, Vetrov, D and Rother, C (2015). Inferring M-best diverse labelings in a single one. Proceedings of the IEEE International Conference on Computer Vision. 2015 Inter 1814–1822
Kirillov, A, Levinkov, E, Andres, B, Savchynskyy, B and Rother, C (2017). InstanceCut: From edges to instances with MultiCut. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 7322–7331
Schelten, K, Nowozin, S, Jancsary, J, Rother, C and Roth, S (2015). Interleaved regression tree field cascades for blind image deconvolution. Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015. 494–501
Mund, J, Michel, F, Dieke-Meier, F, Fricke, H, Meyer, L and Rother, C (2016). Introducing LiDAR Point Cloud-based Object Classification for Safer Apron Operations. International Symposium on Enhanced Solutions for Aircraft and Vehicle Surveillance Applications. https://goo.gl/28Yoqh
Hosseini Jafari, O, Mustikovela, S Karthik, Pertsch, K, Brachmann, E and Rother, C (2019). iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 11363 LNCS 477–492
Levinkov, E, Uhrig, J, Tang, S, Omran, M, Insafutdinov, E, Kirillov, A, Rother, C, Brox, T, Schiele, B and Andres, B (2017). Joint graph decomposition & node labeling: Problem, algorithms, applications. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. 2017-Janua 1904–1912
Vicente, S, Kolmogorov, V and Rother, C (2009). Joint optimization of segmentation and appearance models. Proceedings of the IEEE International Conference on Computer Vision. 755–762
Kirillov, A, Schlesinger, D, Zheng, S, Savchynskyy, B, Torr, P H S and Rother, C (2017). Joint training of generic CNN-CRF models with stochastic optimization. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10112 LNCS 221–236. http://host.robots.ox.ac.uk:8080/leaderboard
Krull, A, Brachmann, E, Michel, F, Yang, M Ying, Gumhold, S and Rother, C (2015). Learning analysis-by-synthesis for 6d pose estimation in RGB-D images. Proceedings of the IEEE International Conference on Computer Vision. 2015 Inter 954–962
Jancsary, J, Nowozin, S and Rother, C (2013). Learning convex QP relaxations for structured prediction. 30th International Conference on Machine Learning, ICML 2013. 1952–1960

Pages