52 citations · 59 across the 4 of their papers we have counts for
5 papers
SynCity: Training-Free Generation of 3D Worlds
Paul Engstler, Aleksandar Shtedritski, Iro Laina +2
We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision…
SHIC: Shape-Image Correspondences with no Keypoint Supervision
Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi
Canonical surface mapping generalizes keypoint detection by assigning each pixel of an object to a corresponding point in a 3D template. Popularised by DensePose for the analysis o…
PaperQA: Retrieval-Augmented Generative Agent for Scientific Research
Jakub Lála, Odhran O'Donoghue, Aleksandar Shtedritski +3
Large Language Models (LLMs) generalize well across language tasks, but suffer from hallucinations and uninterpretability, making it difficult to assess their accuracy without grou…
BioPlanner: Automatic Evaluation of LLMs on Protocol Planning in Biology
Odhran O'Donoghue, Aleksandar Shtedritski, John Ginger +4
The ability to automatically generate accurate protocols for scientific experiments would represent a major step towards the automation of science. Large Language Models (LLMs) hav…
What does CLIP know about a red circle? Visual prompt engineering for VLMs
Aleksandar Shtedritski, Christian Rupprecht, Andrea Vedaldi
Large-scale Vision-Language Models, such as CLIP, learn powerful image-text representations that have found numerous applications, from zero-shot classification to text-to-image ge…