no code implementations • 31 Jul 2023 • Elia Peruzzo, Willi Menapace, Vidit Goel, Federica Arrigoni, Hao Tang, Xingqian Xu, Arman Chopikyan, Nikita Orlov, Yuxiao Hu, Humphrey Shi, Nicu Sebe, Elisa Ricci
This paper advances the state of the art in this emerging research domain by proposing the first approach for Interactive NP.
2 code implementations • CVPR 2023 • Jitesh Jain, Jiachen Li, MangTik Chiu, Ali Hassani, Nikita Orlov, Humphrey Shi
However, such panoptic architectures do not truly unify image segmentation because they need to be trained individually on the semantic, instance, or panoptic segmentation to achieve the best performance.
Ranked #1 on Panoptic Segmentation on COCO minival
no code implementations • 27 Sep 2022 • Yulin Wang, Yang Yue, Xinhong Xu, Ali Hassani, Victor Kulikov, Nikita Orlov, Shiji Song, Humphrey Shi, Gao Huang
Recent research has revealed that reducing the temporal and spatial redundancy are both effective approaches towards efficient video recognition, e. g., allocating the majority of computation to a task-relevant subset of frames or the most valuable image regions of each frame.
1 code implementation • CVPR 2022 • Xu Ma, Yuqian Zhou, Xingqian Xu, Bin Sun, Valerii Filev, Nikita Orlov, Yun Fu, Humphrey Shi
Image rasterization is a mature technique in computer graphics, while image vectorization, the reverse path of rasterization, remains a major challenge.
1 code implementation • CVPR 2022 • Yulin Wang, Yang Yue, Yuanze Lin, Haojun Jiang, Zihang Lai, Victor Kulikov, Nikita Orlov, Humphrey Shi, Gao Huang
Recent works have shown that the computational efficiency of video recognition can be significantly improved by reducing the spatial redundancy.
1 code implementation • arXiv 2021 • Jitesh Jain, Anukriti Singh, Nikita Orlov, Zilong Huang, Jiachen Li, Steven Walton, Humphrey Shi
To achieve this, we propose SeMask, a simple and effective framework that incorporates semantic information into the encoder with the help of a semantic attention operation.
Ranked #10 on Semantic Segmentation on Cityscapes val
no code implementations • 24 Oct 2019 • Dmitry Rodin, Nikita Orlov
Our method divides the document into blocks and collects luminance features from the original image and black-white strokes histograms of the binarized image.
no code implementations • 14 Aug 2019 • Alexander Filonenko, Konstantin Gudkov, Aleksei Lebedev, Nikita Orlov, Ivan Zagaynov
The basic component of it is a convolutional neural network which works in a fully-convolutional manner and produces results at multiple scales.