Deep hierarchical semantic segmentation
Humans are able to recognize structured relations in observation, allowing us to decompose
complex scenes into simpler parts and abstract the visual world in multiple levels. However …
complex scenes into simpler parts and abstract the visual world in multiple levels. However …
Semantic-sam: Segment and recognize anything at any granularity
In this paper, we introduce Semantic-SAM, a universal image segmentation model to enable
segment and recognize anything at any desired granularity. Our model offers two key …
segment and recognize anything at any desired granularity. Our model offers two key …
Deep learning technique for human parsing: A survey and outlook
Human parsing aims to partition humans in image or video into multiple pixel-level semantic
parts. In the last decade, it has gained significantly increased interest in the computer vision …
parts. In the last decade, it has gained significantly increased interest in the computer vision …
Unihcp: A unified model for human-centric perceptions
Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …
person re-identification, etc.) play a key role in industrial applications of visual models. While …
Towards real-world prohibited item detection: A large-scale x-ray benchmark
Automatic security inspection using computer vision technology is a challenging task in real-
world scenarios due to various factors, including intra-class variance, class imbalance, and …
world scenarios due to various factors, including intra-class variance, class imbalance, and …
Logicseg: Parsing visual semantics with neural logic learning and reasoning
Current high-performance semantic segmentation models are purely data-driven sub-
symbolic approaches and blind to the structured nature of the visual world. This is in stark …
symbolic approaches and blind to the structured nature of the visual world. This is in stark …
Differentiable multi-granularity human representation learning for instance-aware human semantic parsing
To address the challenging task of instance-aware human part parsing, a new bottom-up
regime is proposed to learn category-level human semantic segmentation as well as multi …
regime is proposed to learn category-level human semantic segmentation as well as multi …
Differentiable multi-granularity human parsing
In this work, we study the challenging problem of instance-aware human body part parsing.
We introduce a new bottom-up regime which achieves the task through learning category …
We introduce a new bottom-up regime which achieves the task through learning category …
A Human Body Part Semantic Segmentation Enabled Parsing for Human Pose Estimation
A Verma, V Tiwari, M Lovanshi… - Proceedings of the 2023 …, 2023 - dl.acm.org
Human Body Part Semantic Segmentation and Human Pose estimation are considered to
be essential for understanding human behaviours. Both of these tasks are correlated with …
be essential for understanding human behaviours. Both of these tasks are correlated with …
Panoptic-partformer: Learning a unified model for panoptic part segmentation
Abstract Panoptic Part Segmentation (PPS) aims to unify panoptic segmentation and part
segmentation into one task. Previous work mainly utilizes separated approaches to handle …
segmentation into one task. Previous work mainly utilizes separated approaches to handle …