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A review on 2D instance segmentation based on deep neural networks
W Gu, S Bai, L Kong - Image and Vision Computing, 2022 - Elsevier
Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …
which is one of the pivotal technologies in many domains, such as natural scenes …
Recent advances in open set recognition: A survey
In real-world recognition/classification tasks, limited by various objective factors, it is usually
difficult to collect training samples to exhaust all classes when training a recognizer or …
difficult to collect training samples to exhaust all classes when training a recognizer or …
Learning open-world object proposals without learning to classify
Object proposals have become an integral pre-processing step of many vision pipelines
including object detection, weakly supervised detection, object discovery, tracking, etc …
including object detection, weakly supervised detection, object discovery, tracking, etc …
Towards unsupervised object detection from lidar point clouds
L Zhang, AJ Yang, Y ** and 3D object discovery
To autonomously navigate and plan interactions in real-world environments, robots require
the ability to robustly perceive and map complex, unstructured surrounding scenes. Besides …
the ability to robustly perceive and map complex, unstructured surrounding scenes. Besides …
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 …
Shapemask: Learning to segment novel objects by refining shape priors
Instance segmentation aims to detect and segment individual objects in a scene. Most
existing methods rely on precise mask annotations of every category. However, it is difficult …
existing methods rely on precise mask annotations of every category. However, it is difficult …
Delving into shape-aware zero-shot semantic segmentation
Thanks to the impressive progress of large-scale vision-language pretraining, recent
recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a …
recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a …
Identifying unknown instances for autonomous driving
In the past few years, we have seen great progress in perception algorithms, particular
through the use of deep learning. However, most existing approaches focus on a few …
through the use of deep learning. However, most existing approaches focus on a few …
Opental: Towards open set temporal action localization
Abstract Temporal Action Localization (TAL) has experienced remarkable success under the
supervised learning paradigm. However, existing TAL methods are rooted in the closed set …
supervised learning paradigm. However, existing TAL methods are rooted in the closed set …