A survey on open-vocabulary detection and segmentation: Past, present, and future

C Zhu, L Chen - IEEE Transactions on Pattern Analysis and …, 2024 - ieeexplore.ieee.org
As the most fundamental scene understanding tasks, object detection and segmentation
have made tremendous progress in deep learning era. Due to the expensive manual …

DST-Det: Open-Vocabulary Object Detection via Dynamic Self-Training

S Xu, X Li, S Wu, W Zhang, Y Tong… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Open-vocabulary object detection (OVOD) aims to detect the objects beyond the set of
classes observed during training. This work introduces a straightforward and efficient …

Affinity3D: Propagating Instance-Level Semantic Affinity for Zero-Shot Point Cloud Semantic Segmentation

H Liu, J Zhuo, C Liang, J Chen, H Ma - Proceedings of the 32nd ACM …, 2024 - dl.acm.org
Zero-shot point cloud semantic segmentation aims to recognize novel classes at the point
level. Previous methods mainly transfer excellent zero-shot generalization capabilities from …

Investigating Robustness of Open-Vocabulary Foundation Object Detectors under Distribution Shifts

PC Chhipa, K De, MS Chippa, R Saini… - arXiv preprint arXiv …, 2024 - arxiv.org
The challenge of Out-Of-Distribution (OOD) robustness remains a critical hurdle towards
deploying deep vision models. Open-vocabulary object detection extends the capabilities of …

[PDF][PDF] Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts

R Saini, M Liwicki - arXiv preprint arXiv:2405.14874, 2024 - openreview.net
The challenge of Out-Of-Distribution (OOD) robustness remains a critical hurdle towards
deploying deep vision models. Vision-Language Models (VLMs) have recently achieved …