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Hands-on Bayesian neural networks—A tutorial for deep learning users
Modern deep learning methods constitute incredibly powerful tools to tackle a myriad of
challenging problems. However, since deep learning methods operate as black boxes, the …
challenging problems. However, since deep learning methods operate as black boxes, the …
Artificial intelligence in the creative industries: a review
This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …
applications in the context of the creative industries. A brief background of AI, and …
Voxformer: Sparse voxel transformer for camera-based 3d semantic scene completion
Humans can easily imagine the complete 3D geometry of occluded objects and scenes. This
appealing ability is vital for recognition and understanding. To enable such capability in AI …
appealing ability is vital for recognition and understanding. To enable such capability in AI …
A survey on 3d gaussian splatting
3D Gaussian splatting (GS) has recently emerged as a transformative technique in the realm
of explicit radiance field and computer graphics. This innovative approach, characterized by …
of explicit radiance field and computer graphics. This innovative approach, characterized by …
Depth-regularized optimization for 3d gaussian splatting in few-shot images
This paper presents a method to optimize Gaussian splatting with a limited number of
images while avoiding overfitting. Representing a 3D scene by combining numerous …
images while avoiding overfitting. Representing a 3D scene by combining numerous …
Panoocc: Unified occupancy representation for camera-based 3d panoptic segmentation
Comprehensive modeling of the surrounding 3D world is crucial for the success of
autonomous driving. However existing perception tasks like object detection road structure …
autonomous driving. However existing perception tasks like object detection road structure …
Monoscene: Monocular 3d semantic scene completion
MonoScene proposes a 3D Semantic Scene Completion (SSC) framework, where the dense
geometry and semantics of a scene are inferred from a single monocular RGB image …
geometry and semantics of a scene are inferred from a single monocular RGB image …
Computer vision applications in construction: Current state, opportunities & challenges
Thousands of images and videos are collected from construction projects during
construction. These contain valuable data that, if harnessed efficiently, can help automate or …
construction. These contain valuable data that, if harnessed efficiently, can help automate or …
Deep learning for 3d point clouds: A survey
Point cloud learning has lately attracted increasing attention due to its wide applications in
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …
many areas, such as computer vision, autonomous driving, and robotics. As a dominating …
Shapeformer: Transformer-based shape completion via sparse representation
We present ShapeFormer, a transformer-based network that produces a distribution of
object completions, conditioned on incomplete, and possibly noisy, point clouds. The …
object completions, conditioned on incomplete, and possibly noisy, point clouds. The …