03.01.2024
MCML at WACV 2024
Seven Accepted Papers
IEEE/CVF Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, Jan 04-08, 2024
We are happy to announce that MCML researchers have contributed a total of 7 papers to WACV 2024. Congrats to our researchers!
Main Track (7 papers)
M. Bernhard • R. Amoroso • Y. Kindermann • M. Schubert • L. Baraldi • R. Cucchiara • V. Tresp
What's Outside the Intersection? Fine-grained Error Analysis for Semantic Segmentation Beyond IoU.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
What's Outside the Intersection? Fine-grained Error Analysis for Semantic Segmentation Beyond IoU.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
M. Brahimi • B. Haefner • T. Yenamandra • B. Goldluecke • D. Cremers
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
S. Klenk • D. Bonello • L. Koestler • N. Araslanov • D. Cremers
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
Masked Event Modeling: Self-Supervised Pretraining for Event Cameras.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
U. Sahin • H. Li • Q. Khan • D. Cremers • V. Tresp
Enhancing Multimodal Compositional Reasoning of Visual Language Models With Generative Negative Mining.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
Enhancing Multimodal Compositional Reasoning of Visual Language Models With Generative Negative Mining.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
T. Weber • M. Ingrisch • B. Bischl • D. Rügamer
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
Constrained Probabilistic Mask Learning for Task-specific Undersampled MRI Reconstruction.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
T. Tewari • N. Yang • F. Bernard • C. Theobalt • D. Cremers
FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
FIRe: Fast Inverse Rendering Using Directional and Signed Distance Functions.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI
G. Zhang • Y. Zhang • K. Zhang • V. Tresp
Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning.
WACV 2024 - IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, Hawaii, Jan 04-08, 2024. DOI GitHub
Related
21.07.2026
Timo Heiß Receives Best Student Paper Award at XAI 2026
Timo Heiß receives the Best Student Paper Award at XAI 2026 for research on improving feature effect estimation in explainable AI.
21.07.2026
The Learning Rate Does More Than Set the Pace
New ICML 2026 research by Gitta Kutyniok and her team shows how learning rates balance competing biases that shape neural network generalization.
20.07.2026
How Fair Does AI Seem in Job Interviews?
A new study by Enkelejda Kasneci examines how applicants perceive fairness in AI-driven job interviews.
