Jack Valmadre

An accurate detection is not all you need to combat label noise in web-noisy dataset

Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor and Kevin McGuinness

ECCV 2024, Paper, Code
Oops, I sampled it again: Reinterpreting confidence intervals in few-shot learning

Raphaël Lafargue, Luke A. Smith, Franck Vermet, Matthias Löwe, Ian Reid, Jack Valmadre and Vincent Gripon

TMLR 2024, Paper, Code, Video
On skip connections and normalisation layers in deep optimisation

Lachlan E. MacDonald, Jack Valmadre, Hemanth Saratchandran and Simon Lucey

NeurIPS 2024, Paper, Code
On progressive sharpening, flat minima and generalisation

Lachlan E. MacDonald, Jack Valmadre and Simon Lucey

Tech report 2023, Paper
Hierarchical classification at multiple operating points

Jack Valmadre

NeurIPS 2022, Paper, Code
Learning with neighbor consistency for noisy labels

Ahmet Iscen, Jack Valmadre, Anurag Arnab and Cordelia Schmid

CVPR 2022, Paper, Code
Local metrics for multi-object tracking

Jack Valmadre, Alex Bewley, Jonathan Huang, Chen Sun, Cristian Sminchisescu and Cordelia Schmid

Tech report 2021, Paper, Code
Long-term tracking in the wild: A benchmark

Jack Valmadre*, Luca Bertinetto*, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold W. M. Smeulders, Philip H. S. Torr and Efstratios Gavves*

ECCV 2018, Paper, Toolkit, State of the art, Evaluation server
End-to-end representation learning for Correlation Filter based tracking

Jack Valmadre*, Luca Bertinetto*, João F. Henriques, Andrea Vedaldi and Philip H. S. Torr

CVPR 2017, Paper
Learning feed-forward one-shot learners

Luca Bertinetto*, João F. Henriques*, Jack Valmadre*, Philip H. S. Torr and Andrea Vedaldi

NeurIPS 2016, arXiv
Fully-convolutional Siamese networks for object tracking

Luca Bertinetto*, Jack Valmadre*, João F. Henriques, Andrea Vedaldi and Philip H.S. Torr

ECCV Workshop 2016, arXiv
Staple: Complementary learners for real-time tracking

Luca Bertinetto, Jack Valmadre, Stuart Golodetz, Ondrej Miksik and Philip H. S. Torr

CVPR 2016
Dense semantic correspondence where every pixel is a classifier

Hilton Bristow, Jack Valmadre and Simon Lucey

ICCV 2015 (oral)
Closed-form solutions for low-rank non-rigid reconstruction

Jack Valmadre, Sridha Sridharan, Simon Denman, Clinton Fookes and Simon Lucey

DICTA 2015
Learning detectors quickly with stationary statistics

Jack Valmadre, Sridha Sridharan and Simon Lucey

ACCV 2014, Paper, Poster, arXiv
Separable spatiotemporal priors for convex reconstruction of time-varying 3D point clouds

Tomas Simon, Jack Valmadre, Iain Matthews and Yaser Sheikh

ECCV 2014, Publisher
Efficient articulated trajectory reconstruction using dynamic programming and filters

Jack Valmadre, Yingying Zhu, Sridha Sridharan and Simon Lucey

ECCV 2012, Paper, Publisher
General trajectory prior for non-rigid reconstruction (with code)

Jack Valmadre and Simon Lucey

CVPR 2012, Paper, Poster, Publisher
Graph rigidity for near-coplanar structure from motion

Jack Valmadre, Ben Upcroft, Sridha Sridharan and Simon Lucey

DICTA 2011, Paper, Poster, Publisher
Deterministic 3D human pose estimation using rigid structure

Jack Valmadre and Simon Lucey

ECCV 2010, Poster, Matlab code, Publisher