1 code implementation • 28 May 2025 • Maksim Kolodiazhnyi, Denis Tarasov, Dmitrii Zhemchuzhnikov, Alexander Nikulin, Ilya Zisman, Anna Vorontsova, Anton Konushin, Vladislav Kurenkov, Danila Rukhovich
Computer-Aided Design (CAD) plays a central role in engineering and manufacturing, making it possible to create precise and editable 3D models.
Ranked #1 on
CAD Reconstruction
on CC3D
no code implementations • 29 Oct 2024 • Timur Mamedov, Anton Konushin, Vadim Konushin
To the best of our knowledge, this is the first work that explores joint training on a mixture of multi-camera and single-camera data in person Re-ID.
Ranked #1 on
Generalizable Person Re-identification
on CUHK03-NP (detected)
(RandPerson->mAP metric, using extra
training data)
1 code implementation • 15 Oct 2024 • Anton Antonov, Andrey Moskalenko, Denis Shepelev, Alexander Krapukhin, Konstantin Soshin, Anton Konushin, Vlad Shakhuro
According to our benchmark, in real-world usage interactive segmentation models may perform worse than it has been reported in the baseline benchmark, and most of the methods are not robust.
no code implementations • 23 Sep 2024 • Bulat Gabdullin, Nina Konovalova, Nikolay Patakin, Dmitry Senushkin, Anton Konushin
Following the visual autoregressive modeling paradigm, we introduce the first autoregressive depth estimation model based on the visual autoregressive transformer.
1 code implementation • 6 Sep 2024 • Maksim Kolodiazhnyi, Anna Vorontsova, Matvey Skripkin, Danila Rukhovich, Anton Konushin
Growing customer demand for smart solutions in robotics and augmented reality has attracted considerable attention to 3D object detection from point clouds.
Ranked #1 on
3D Object Detection
on ScanNet++
(using extra training data)
no code implementations • 21 Jun 2024 • Savva Ignatyev, Nina Konovalova, Daniil Selikhanovych, Oleg Voynov, Nikolay Patakin, Ilya Olkov, Dmitry Senushkin, Alexey Artemov, Anton Konushin, Alexander Filippov, Peter Wonka, Evgeny Burnaev
In order to achieve the alignment of the corresponding parts of the generated objects, we propose to embed these objects into a common latent space and optimize the continuous transitions between these objects.
no code implementations • 25 Apr 2024 • Arina Varlamova, Valery Belotsky, Grigory Novikov, Anton Konushin, Evgeny Sidorov
Detection of malignant lesions on mammography images is extremely important for early breast cancer diagnosis.
no code implementations • 9 Feb 2024 • Andrey Moskalenko, Vlad Shakhuro, Anna Vorontsova, Anton Konushin, Anton Antonov, Alexander Krapukhin, Denis Shepelev, Konstantin Soshin
Based on the performance with such adversarial user inputs, we assess the robustness of interactive segmentation models w. r. t click positions.
1 code implementation • CVPR 2024 • Maxim Kolodiazhnyi, Anna Vorontsova, Anton Konushin, Danila Rukhovich
Semantic, instance, and panoptic segmentation of 3D point clouds have been addressed using task-specific models of distinct design.
Ranked #1 on
Panoptic Segmentation
on ScanNet
no code implementations • CVPR 2022 • Nikolay Patakin, Mikhail Romanov, Anna Vorontsova, Mikhail Artemyev, Anton Konushin
On the contrary, we propose GP$^{2}$, General-Purpose and Geometry-Preserving training scheme, and show that conventional SVDE models can learn correct shifts themselves without any post-processing, benefiting from using stereo data even in the geometry-preserving setting.
1 code implementation • CVPR 2023 • Dmitry Senushkin, Nikolay Patakin, Arseny Kuznetsov, Anton Konushin
In this work, we propose using a condition number of a linear system of gradients as a stability criterion of an MTL optimization.
no code implementations • 13 Feb 2023 • Danil Galeev, Polina Popenova, Anna Vorontsova, Anton Konushin
Recent advances in interactive segmentation (IS) allow speeding up and simplifying image editing and labeling greatly.
no code implementations • 6 Feb 2023 • Danila Rukhovich, Anna Vorontsova, Anton Konushin
Our model with early feature fusion, which we refer to as TR3D+FF, outperforms existing 3D object detection approaches on the SUN RGB-D dataset.
Ranked #2 on
3D Object Detection
on ScanNet++
no code implementations • 6 Feb 2023 • Maksim Kolodiazhnyi, Anna Vorontsova, Anton Konushin, Danila Rukhovich
Most 3D instance segmentation methods exploit a bottom-up strategy, typically including resource-exhaustive post-processing.
Ranked #3 on
3D Instance Segmentation
on STPLS3D
no code implementations • 10 Oct 2022 • Anna Sokolova, Filipp Nikitin, Anna Vorontsova, Anton Konushin
Processing large indoor scenes is a challenging task, as scan registration and camera trajectory estimation methods accumulate errors across time.
2 code implementations • 1 Dec 2021 • Danila Rukhovich, Anna Vorontsova, Anton Konushin
Existing 3D object detection methods make prior assumptions on the geometry of objects, and we argue that it limits their generalization ability.
Ranked #3 on
3D Object Detection
on ScanNet++
2 code implementations • 2 Jun 2021 • Danila Rukhovich, Anna Vorontsova, Anton Konushin
To address this problem, we propose ImVoxelNet, a novel fully convolutional method of 3D object detection based on monocular or multi-view RGB images.
Ranked #2 on
Monocular 3D Object Detection
on SUN RGB-D
Monocular 3D Object Detection
Monocular 3D Object Detection (10 / NYU-37)
+4
5 code implementations • 12 Feb 2021 • Konstantin Sofiiuk, Ilia A. Petrov, Anton Konushin
We find that the models trained on a combination of COCO and LVIS with diverse and high-quality annotations show performance superior to all existing models.
Ranked #6 on
Interactive Segmentation
on DAVIS
no code implementations • 13 Jan 2021 • Anton Konushin, Boris Faizov, Vlad Shakhuro
Such training data is obtained by embedding synthetic images of signs in the real photos.
no code implementations • 25 Sep 2020 • Mikhail Romanov, Nikolay Patatkin, Anna Vorontsova, Sergey Nikolenko, Anton Konushin, Dmitry Senyushkin
Our work shows that a model trained on this data along with conventional datasets can gain accuracy while predicting correct scene geometry.
no code implementations • 18 Jun 2020 • Danil Galeev, Konstantin Sofiiuk, Danila Rukhovich, Mikhail Romanov, Olga Barinova, Anton Konushin
Based on this finding, we propose LayerMatch scheme for approximating the representation of a GAN generator that can be used for unsupervised domain-specific pretraining.
no code implementations • 1 Jun 2020 • Konstantin Sofiiuk, Polina Popenova, Anton Konushin
Image harmonization is an important step in photo editing to achieve visual consistency in composite images by adjusting the appearances of foreground to make it compatible with background.
no code implementations • 18 May 2020 • Dmitry Senushkin, Mikhail Romanov, Ilia Belikov, Anton Konushin, Nikolay Patakin
Our second contribution is a novel training strategy that allows us to train on a semi-dense sensor data when the ground truth depth map is not available.
Ranked #1 on
Depth Completion
on Matterport3D
no code implementations • 12 May 2020 • Danila Rukhovich, Konstantin Sofiiuk, Danil Galeev, Olga Barinova, Anton Konushin
Deep learning-based detectors usually produce a redundant set of object bounding boxes including many duplicate detections of the same object.
Ranked #1 on
Object Detection
on WiderPerson
2 code implementations • CVPR 2020 • Konstantin Sofiiuk, Ilia Petrov, Olga Barinova, Anton Konushin
We propose f-BRS (feature backpropagating refinement scheme) that solves an optimization problem with respect to auxiliary variables instead of the network inputs, and requires running forward and backward pass just for a small part of a network.
Ranked #8 on
Interactive Segmentation
on SBD
no code implementations • 11 Dec 2019 • Igor Slinko, Anna Vorontsova, Dmitry Zhukov, Olga Barinova, Anton Konushin
We train visual odometry model on synthetic data and do not use ground truth poses hence this model can be considered unsupervised.
no code implementations • 10 Oct 2019 • David Prokhorov, Dmitry Zhukov, Olga Barinova, Anna Vorontsova, Anton Konushin
We find that while in many cases the accuracy of SLAM is very good, the robustness is still an issue.
no code implementations • 26 Sep 2019 • Pavel Kirsanov, Airat Gaskarov, Filipp Konokhov, Konstantin Sofiiuk, Anna Vorontsova, Igor Slinko, Dmitry Zhukov, Sergey Bykov, Olga Barinova, Anton Konushin
We present a novel dataset for training and benchmarking semantic SLAM methods.
no code implementations • ICCV 2019 • Konstantin Sofiiuk, Olga Barinova, Anton Konushin
Given an input image and a point $(x, y)$, it generates a mask for the object located at $(x, y)$.
Ranked #9 on
Panoptic Segmentation
on Mapillary val
2 code implementations • 12 Sep 2019 • Nina Tuluptceva, Bart Bakker, Irina Fedulova, Anton Konushin
We present a novel method for image anomaly detection, where algorithms that use samples drawn from some distribution of "normal" data, aim to detect out-of-distribution (abnormal) samples.
no code implementations • 16 Jul 2019 • Igor Slinko, Anna Vorontsova, Filipp Konokhov, Olga Barinova, Anton Konushin
Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene.
no code implementations • 20 Nov 2018 • Nikita Durasov, Mikhail Romanov, Valeriya Bubnova, Pavel Bogomolov, Anton Konushin
Monocular depth estimation is the task of obtaining a measure of distance for each pixel using a single image.
Indoor Monocular Depth Estimation
Monocular Depth Estimation
no code implementations • 17 Oct 2017 • Anna Sokolova, Anton Konushin
In this paper, we present a new pose-based convolutional neural network model for gait recognition.