From the 1 of 15 linked papers with an AI index.
15 papers
Improved Robustness from Biologically Inspired Sparse Contrast Representations
Lorena Stracke, Lia Nimmermann, Shashank Agnihotri +3
The paper introduces a fixed, model‑agnostic preprocessing step inspired by retinal processing that applies color remapping and local contrast extraction to create sparse image rep…
Beware of Aliases -- Signal Preservation is Crucial for Robust Image Restoration
Shashank Agnihotri, Julia Grabinski, Janis Keuper +1
Image restoration networks are usually comprised of an encoder and a decoder, responsible for aggregating image content from noisy, distorted data and to restore clean, undistorted…
Images as Tables: In-Context Learning with TabPFN for Low-Data Detection of AI-Generated Images
Jan Philip Walter, Shashank Agnihotri, Margret Keuper
AI-generated image detection is a moving-target problem: detectors trained on one generator often fail when a new generator appears, and only a few labeled examples are available.…
RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
Victor Oei, Jenny Schmalfuss, Lukas Mehl +5
Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image corruptions like noise or rain. Hen…
GeoDiv: Framework For Measuring Geographical Diversity In Text-To-Image Models
Abhipsa Basu, Mohana Singh, Shashank Agnihotri +2
Text-to-image (T2I) models are rapidly gaining popularity, yet their outputs often lack geographical diversity, reinforce stereotypes, and misrepresent regions. Given their broad r…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…