no code implementations • 22 Oct 2014 • German Ros, Jose Alvarez, Julio Guerrero
To this end we propose the Robust Decomposition with Constrained Rank (RD-CR), a proximal gradient based method that enforces the rank constraints inherent to motion estimation.
no code implementations • 17 Jun 2016 • Jose Alvarez, Lars Petersson
Deep learning and convolutional neural networks (ConvNets) have been successfully applied to most relevant tasks in the computer vision community.
1 code implementation • CVPR 2022 • Hongxu Yin, Arash Vahdat, Jose Alvarez, Arun Mallya, Jan Kautz, Pavlo Molchanov
A-ViT achieves this by automatically reducing the number of tokens in vision transformers that are processed in the network as inference proceeds.
no code implementations • ICCV 2023 • Yanwei Li, Zhiding Yu, Jonah Philion, Anima Anandkumar, Sanja Fidler, Jiaya Jia, Jose Alvarez
In this work, we present an end-to-end framework for camera-based 3D multi-object tracking, called DQTrack.
no code implementations • 25 Jun 2023 • Anna Bair, Hongxu Yin, Maying Shen, Pavlo Molchanov, Jose Alvarez
Robustness and compactness are two essential attributes of deep learning models that are deployed in the real world.
1 code implementation • 8 Aug 2023 • Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Animashree Anandkumar, Jiaya Jia, Jose Alvarez
For 3D object detection, we instantiate this method as FocalFormer3D, a simple yet effective detector that excels at excavating difficult objects and improving prediction recall.
Ranked #8 on 3D Object Detection on nuScenes