HASSOD: Hierarchical adaptive self-supervised object detection

S Cao, D Joshi, L Gui, YX Wang - Advances in Neural …, 2023‏ - proceedings.neurips.cc
The human visual perception system demonstrates exceptional capabilities in learning
without explicit supervision and understanding the part-to-whole composition of objects …

Exploring transformers for open-world instance segmentation

J Wu, Y Jiang, B Yan, H Lu… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Open-world instance segmentation is a rising task, which aims to segment all objects in the
image by learning from a limited number of base-category objects. This task is challenging …

Eliminating and mining strategies for open-world object proposal

C Wang, G Wang, Q Zhang, P Guo, W Liu, X Wang - Neurocomputing, 2024‏ - Elsevier
Object proposal serves as a crucial pre-task of many image and video understanding
applications. However, modern approaches for object proposal are typically based on …

SOS: Segment Object System for Open-World Instance Segmentation with Object Priors

C Wilms, T Rolff, M Hillemann, R Johanson… - … on Computer Vision, 2024‏ - Springer
We propose an approach for Open-World Instance Segmentation (OWIS), a task that aims to
segment arbitrary unknown objects in images by generalizing from a limited set of annotated …

Generalized Class Discovery in Instance Segmentation

CM Hoang, Y Lee, B Kang - arxiv preprint arxiv:2502.08149, 2025‏ - arxiv.org
This work addresses the task of generalized class discovery (GCD) in instance
segmentation. The goal is to discover novel classes and obtain a model capable of …

st-DenseViT: A Weakly Supervised Spatiotemporal Vision Transformer for Dense Prediction of Dynamic Brain Networks

B Kazemivash, P Suresh, DH Ye, A Iraji, J Liu, S Plis… - bioRxiv, 2024‏ - biorxiv.org
Objective Modeling dynamic neuronal activity within brain networks enables the precise
tracking of rapid temporal fluctuations across different brain regions. However, current …