activity
20162025
most citedRecovering the Missing Link: Predicting Class-Attribute Associations for Unsupervised Zero-Shot Learning

22 citations · 35 across the 8 of their papers we have counts for

collaborators

23 papers

cs.CV2024

Comb, Prune, Distill: Towards Unified Pruning for Vision Model Compression

Jonas Schmitt, Ruiping Liu, Junwei Zheng +2

Lightweight and effective models are essential for devices with limited resources, such as intelligent vehicles. Structured pruning offers a promising approach to model compression…

cs.CV2024

Open Panoramic Segmentation

Junwei Zheng, Ruiping Liu, Yufan Chen +5

Panoramic images, capturing a 360° field of view (FoV), encompass omnidirectional spatial information crucial for scene understanding. However, it is not only costly to obtain trai…

cs.CV2024

Referring Atomic Video Action Recognition

Kunyu Peng, Jia Fu, Kailun Yang +8

We introduce a new task called Referring Atomic Video Action Recognition (RAVAR), aimed at identifying atomic actions of a particular person based on a textual description and the…

cs.CV2024

Anatomy-guided Pathology Segmentation

Alexander Jaus, Constantin Seibold, Simon Reiß +7

Pathological structures in medical images are typically deviations from the expected anatomy of a patient. While clinicians consider this interplay between anatomy and pathology, r…

eess.IV2024

Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods

Zdravko Marinov, Moon Kim, Jens Kleesiek +1

Interactive segmentation plays a crucial role in accelerating the annotation, particularly in domains requiring specialized expertise such as nuclear medicine. For example, annotat…

cs.HC202424 cited

Chart4Blind: An Intelligent Interface for Chart Accessibility Conversion

Omar Moured, Morris Baumgarten-Egemole, Alina Roitberg +3

In a world driven by data visualization, ensuring the inclusive accessibility of charts for Blind and Visually Impaired (BVI) individuals remains a significant challenge. Charts ar…