Maxim Berman

According to our database, Maxim Berman authored at least 19 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations.

Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union.

Zifu Wang, Maxim Berman, Amal Rannen-Triki, Philip H. S. Torr, Devis Tuia, Tinne Tuytelaars, Luc Van Gool, Jiaqian Yu, Matthew B. Blaschko

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2020

Optimization for Medical Image Segmentation: Theory and Practice When Evaluating With Dice Score or Jaccard Index.

Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko

IEEE Trans. Medical Imaging, 2020

Discriminative Training of Conditional Random Fields with Probably Submodular Constraints.

Maxim Berman, Matthew B. Blaschko

Int. J. Comput. Vis., 2020

AOWS: Adaptive and Optimal Network Width Search With Latency Constraints.

Maxim Berman, Leonid Pishchulin, Ning Xu, Matthew B. Blaschko, Gérard G. Medioni

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory & Practice.

Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko

CoRR, 2019

Generating superpixels using deep image representations.

Thomas Verelst, Matthew B. Blaschko, Maxim Berman

CoRR, 2019

MultiGrain: a unified image embedding for classes and instances.

Maxim Berman, Hervé Jégou, Andrea Vedaldi, Iasonas Kokkinos, Matthijs Douze

CoRR, 2019

Optimizing the Dice Score and Jaccard Index for Medical Image Segmentation: Theory and Practice.

Jeroen Bertels, Tom Eelbode, Maxim Berman, Dirk Vandermeulen, Frederik Maes, Raf Bisschops, Matthew B. Blaschko

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Function Norms for Neural Networks.

Amal Rannen-Triki, Maxim Berman, Vladimir Kolmogorov, Matthew B. Blaschko

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

A Bayesian Optimization Framework for Neural Network Compression.

Xingchen Ma, Amal Rannen Triki, Maxim Berman, Christos Sagonas, Jacques Calì, Matthew B. Blaschko

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Adaptive Compression-based Lifelong Learning.

Shivangi Srivastava, Maxim Berman, Matthew B. Blaschko, Devis Tuia

Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018

Yes, IoU loss is submodular - as a function of the mispredictions.

Maxim Berman, Matthew B. Blaschko, Amal Rannen Triki, Jiaqian Yu

CoRR, 2018

Supermodular Locality Sensitive Hashes.

Maxim Berman, Matthew B. Blaschko

CoRR, 2018

Efficient semantic image segmentation with superpixel pooling.

Mathijs Schuurmans, Maxim Berman, Matthew B. Blaschko

CoRR, 2018

The Lovász-Softmax Loss: A Tractable Surrogate for the Optimization of the Intersection-Over-Union Measure in Neural Networks.

Maxim Berman, Amal Rannen Triki, Matthew B. Blaschko

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Stochastic Weighted Function Norm Regularization.

Amal Rannen Triki, Maxim Berman, Matthew B. Blaschko

CoRR, 2017

Optimization of the Jaccard index for image segmentation with the Lovász hinge.

Maxim Berman, Matthew B. Blaschko

CoRR, 2017

2016

Monocular Surface Reconstruction Using 3D Deformable Part Models.

Stefan Kinauer, Maxim Berman, Iasonas Kokkinos

Proceedings of the Computer Vision - ECCV 2016 Workshops, 2016