A survey on open-vocabulary detection and segmentation: Past, present, and future
As the most fundamental scene understanding tasks, object detection and segmentation
have made tremendous progress in deep learning era. Due to the expensive manual …
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 …
classes observed during training. This work introduces a straightforward and efficient …
Affinity3D: Propagating Instance-Level Semantic Affinity for Zero-Shot Point Cloud Semantic Segmentation
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 …
level. Previous methods mainly transfer excellent zero-shot generalization capabilities from …
Investigating Robustness of Open-Vocabulary Foundation Object Detectors under Distribution Shifts
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 …
deploying deep vision models. Open-vocabulary object detection extends the capabilities of …
[PDF][PDF] Open-Vocabulary Object Detectors: Robustness Challenges under Distribution Shifts
The challenge of Out-Of-Distribution (OOD) robustness remains a critical hurdle towards
deploying deep vision models. Vision-Language Models (VLMs) have recently achieved …
deploying deep vision models. Vision-Language Models (VLMs) have recently achieved …