activity
20142023
most citedHigh-Speed Tracking with Kernelized Correlation Filters

5.8k citations · 5.9k across the 4 of their papers we have counts for

collaborators

11 papers

cs.LG2024

HelloFresh: LLM Evaluations on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits

Tim Franzmeyer, Aleksandar Shtedritski, Samuel Albanie +3

Benchmarks have been essential for driving progress in machine learning. A better understanding of LLM capabilities on real world tasks is vital for safe development. Designing ade…

eess.IV20242 cited

RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scans

Mark C. Eid, Pak-Hei Yeung, Madeleine K. Wyburd +2

Two-dimensional (2D) freehand ultrasonography is one of the most commonly used medical imaging modalities, particularly in obstetrics and gynaecology. However, it only captures 2D…

cs.CV2024

Stale Diffusion: Hyper-realistic 5D Movie Generation Using Old-school Methods

Joao F. Henriques, Dylan Campbell, Tengda Han

Two years ago, Stable Diffusion achieved super-human performance at generating images with super-human numbers of fingers. Following the steady decline of its technical novelty, we…

eess.AS2024

A SOUND APPROACH: Using Large Language Models to generate audio descriptions for egocentric text-audio retrieval

Andreea-Maria Oncescu, João F. Henriques, Andrew Zisserman +2

Video databases from the internet are a valuable source of text-audio retrieval datasets. However, given that sound and vision streams represent different "views" of the data, trea…

cs.CV2024

SCENES: Subpixel Correspondence Estimation With Epipolar Supervision

Dominik A. Kloepfer, João F. Henriques, Dylan Campbell

Extracting point correspondences from two or more views of a scene is a fundamental computer vision problem with particular importance for relative camera pose estimation and struc…

cs.SE20242 cited

LangProp: A code optimization framework using Large Language Models applied to driving

Shu Ishida, Gianluca Corrado, George Fedoseev +5

We propose LangProp, a framework for iteratively optimizing code generated by large language models (LLMs), in both supervised and reinforcement learning settings. While LLMs can g…