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Gres: Generalized referring expression segmentation
Abstract Referring Expression Segmentation (RES) aims to generate a segmentation mask
for the object described by a given language expression. Existing classic RES datasets and …
for the object described by a given language expression. Existing classic RES datasets and …
Towards open vocabulary learning: A survey
In the field of visual scene understanding, deep neural networks have made impressive
advancements in various core tasks like segmentation, tracking, and detection. However …
advancements in various core tasks like segmentation, tracking, and detection. However …
[HTML][HTML] Deep-learning-based point cloud semantic segmentation: A survey
R Zhang, Y Wu, W **, X Meng - Electronics, 2023 - mdpi.com
With the rapid development of sensor technologies and the widespread use of laser
scanning equipment, point clouds, as the main data form and an important information …
scanning equipment, point clouds, as the main data form and an important information …
VGSG: Vision-guided semantic-group network for text-based person search
Text-based Person Search (TBPS) aims to retrieve images of target pedestrian indicated by
textual descriptions. It is essential for TBPS to extract fine-grained local features and align …
textual descriptions. It is essential for TBPS to extract fine-grained local features and align …
Rethinking few-shot 3d point cloud semantic segmentation
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS) with a focus on
two significant issues in the state-of-the-art: foreground leakage and sparse point …
two significant issues in the state-of-the-art: foreground leakage and sparse point …
Rethinking prior information generation with clip for few-shot segmentation
Few-shot segmentation remains challenging due to the limitations of its labeling information
for unseen classes. Most previous approaches rely on extracting high-level feature maps …
for unseen classes. Most previous approaches rely on extracting high-level feature maps …
No time to train: Empowering non-parametric networks for few-shot 3d scene segmentation
To reduce the reliance on large-scale datasets recent works in 3D segmentation resort to
few-shot learning. Current 3D few-shot segmentation methods first pre-train models …
few-shot learning. Current 3D few-shot segmentation methods first pre-train models …
Semantic-promoted debiasing and background disambiguation for zero-shot instance segmentation
Zero-shot instance segmentation aims to detect and precisely segment objects of unseen
categories without any training samples. Since the model is trained on seen categories …
categories without any training samples. Since the model is trained on seen categories …
Segpoint: Segment any point cloud via large language model
Despite significant progress in 3D point cloud segmentation, existing methods primarily
address specific tasks and depend on explicit instructions to identify targets, lacking the …
address specific tasks and depend on explicit instructions to identify targets, lacking the …
Bias-compensation augmentation learning for semantic segmentation in UAV networks
In the realm of emergency disaster relief, it is paramount to attain a thorough comprehension
of the semantic information associated with the local disaster scene for strategic rescue path …
of the semantic information associated with the local disaster scene for strategic rescue path …