Backbones-review: Feature extraction networks for deep learning and deep reinforcement learning approaches
To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …
most used technique nowadays. While finding the pattern within the analyzed data …
Convolutions die hard: Open-vocabulary segmentation with single frozen convolutional clip
Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing
objects from an open set of categories in diverse environments. One way to address this …
objects from an open set of categories in diverse environments. One way to address this …
Oneformer: One transformer to rule universal image segmentation
Abstract Universal Image Segmentation is not a new concept. Past attempts to unify image
segmentation include scene parsing, panoptic segmentation, and, more recently, new …
segmentation include scene parsing, panoptic segmentation, and, more recently, new …
Masked-attention mask transformer for universal image segmentation
Image segmentation groups pixels with different semantics, eg, category or instance
membership. Each choice of semantics defines a task. While only the semantics of each task …
membership. Each choice of semantics defines a task. While only the semantics of each task …
A generalist framework for panoptic segmentation of images and videos
Panoptic segmentation assigns semantic and instance ID labels to every pixel of an image.
As permutations of instance IDs are also valid solutions, the task requires learning of high …
As permutations of instance IDs are also valid solutions, the task requires learning of high …
Panoptic segmentation: A review
Image segmentation for video analysis plays an essential role in different research fields
such as smart city, healthcare, computer vision and geoscience, and remote sensing …
such as smart city, healthcare, computer vision and geoscience, and remote sensing …
Cmt-deeplab: Clustering mask transformers for panoptic segmentation
Abstract We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-based
framework for panoptic segmentation designed around clustering. It rethinks the existing …
framework for panoptic segmentation designed around clustering. It rethinks the existing …
Milestones in autonomous driving and intelligent vehicles—part ii: Perception and planning
A growing interest in autonomous driving (AD) and intelligent vehicles (IVs) is fueled by their
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …
promise for enhanced safety, efficiency, and economic benefits. While previous surveys …
Mp-former: Mask-piloted transformer for image segmentation
We present a mask-piloted Transformer which improves masked-attention in Mask2Former
for image segmentation. The improvement is based on our observation that Mask2Former …
for image segmentation. The improvement is based on our observation that Mask2Former …
Moat: Alternating mobile convolution and attention brings strong vision models
This paper presents MOAT, a family of neural networks that build on top of MObile
convolution (ie, inverted residual blocks) and ATtention. Unlike the current works that stack …
convolution (ie, inverted residual blocks) and ATtention. Unlike the current works that stack …