Search Results for author: Jose Alvarez

Found 6 papers, 2 papers with code

FocalFormer3D : Focusing on Hard Instance for 3D Object Detection

1 code implementation8 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.

3D Object Detection Autonomous Driving +3

Adaptive Sharpness-Aware Pruning for Robust Sparse Networks

no code implementations25 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.

Image Classification object-detection +2

AdaViT: Adaptive Tokens for Efficient Vision Transformer

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.

Efficient ViTs Token Reduction

DecomposeMe: Simplifying ConvNets for End-to-End Learning

no code implementations17 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.

Motion Estimation via Robust Decomposition with Constrained Rank

no code implementations22 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.

Motion Estimation Outlier Detection +1

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