Search Results for author: Joao Carreira

Found 16 papers, 5 papers with code

Perceiver: General Perception with Iterative Attention

7 code implementations4 Mar 2021 Andrew Jaegle, Felix Gimeno, Andrew Brock, Andrew Zisserman, Oriol Vinyals, Joao Carreira

The perception models used in deep learning on the other hand are designed for individual modalities, often relying on domain-specific assumptions such as the local grid structures exploited by virtually all existing vision models.

3D Point Cloud Classification Audio Classification +1

A Short Note on the Kinetics-700 Human Action Dataset

no code implementations15 Jul 2019 Joao Carreira, Eric Noland, Chloe Hillier, Andrew Zisserman

We describe an extension of the DeepMind Kinetics human action dataset from 600 classes to 700 classes, where for each class there are at least 600 video clips from different YouTube videos.

Action Classification

Cloud Programming Simplified: A Berkeley View on Serverless Computing

no code implementations9 Feb 2019 Eric Jonas, Johann Schleier-Smith, Vikram Sreekanti, Chia-Che Tsai, Anurag Khandelwal, Qifan Pu, Vaishaal Shankar, Joao Carreira, Karl Krauth, Neeraja Yadwadkar, Joseph E. Gonzalez, Raluca Ada Popa, Ion Stoica, David A. Patterson

Serverless cloud computing handles virtually all the system administration operations needed to make it easier for programmers to use the cloud.

Operating Systems

A Short Note about Kinetics-600

1 code implementation3 Aug 2018 Joao Carreira, Eric Noland, Andras Banki-Horvath, Chloe Hillier, Andrew Zisserman

We describe an extension of the DeepMind Kinetics human action dataset from 400 classes, each with at least 400 video clips, to 600 classes, each with at least 600 video clips.

Action Classification

Massively Parallel Video Networks

no code implementations ECCV 2018 Joao Carreira, Viorica Patraucean, Laurent Mazare, Andrew Zisserman, Simon Osindero

We introduce a class of causal video understanding models that aims to improve efficiency of video processing by maximising throughput, minimising latency, and reducing the number of clock cycles.

Action Recognition Video Understanding

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

24 code implementations CVPR 2017 Joao Carreira, Andrew Zisserman

The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks.

Action Recognition Classification +2

Human Pose Estimation with Iterative Error Feedback

1 code implementation CVPR 2016 Joao Carreira, Pulkit Agrawal, Katerina Fragkiadaki, Jitendra Malik

Hierarchical feature extractors such as Convolutional Networks (ConvNets) have achieved impressive performance on a variety of classification tasks using purely feedforward processing.

Pose Estimation Semantic Segmentation

Learning to See by Moving

no code implementations ICCV 2015 Pulkit Agrawal, Joao Carreira, Jitendra Malik

We show that given the same number of training images, features learnt using egomotion as supervision compare favourably to features learnt using class-label as supervision on visual tasks of scene recognition, object recognition, visual odometry and keypoint matching.

Object Recognition Scene Recognition +1

Lifting Object Detection Datasets into 3D

no code implementations22 Mar 2015 Joao Carreira, Sara Vicente, Lourdes Agapito, Jorge Batista

In particular, acquiring ground truth 3D shapes of objects pictured in 2D images remains a challenging feat and this has hampered progress in recognition-based object reconstruction from a single image.

3D Reconstruction Object Detection +3

Iterated Second-Order Label Sensitive Pooling for 3D Human Pose Estimation

no code implementations CVPR 2014 Catalin Ionescu, Joao Carreira, Cristian Sminchisescu

Recently, the emergence of Kinect systems has demonstrated the benefits of predicting an intermediate body part labeling for 3D human pose estimation, in conjunction with RGB-D imagery.

3D Human Pose Estimation Motion Capture

Reconstructing PASCAL VOC

no code implementations CVPR 2014 Sara Vicente, Joao Carreira, Lourdes Agapito, Jorge Batista

We address the problem of populating object category detection datasets with dense, per-object 3D reconstructions, bootstrapped from class labels, ground truth figure-ground segmentations and a small set of keypoint annotations.

Structure from Motion

Probabilistic Joint Image Segmentation and Labeling

no code implementations NeurIPS 2011 Adrian Ion, Joao Carreira, Cristian Sminchisescu

We present a joint image segmentation and labeling model (JSL) which, given a bag of figure-ground segment hypotheses extracted at multiple image locations and scales, constructs a joint probability distribution over both the compatible image interpretations (tilings or image segmentations) composed from those segments, and over their labeling into categories.

Semantic Segmentation

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