point cloud completion

Kuaishou Large Model

Sep 30, 2021 · Artificial Intelligence

How SnowflakeNet Revolutionizes Point Cloud Completion with Skip‑Transformer

SnowflakeNet introduces a novel Snowflake Point Deconvolution architecture combined with a Skip‑Transformer to explicitly split and refine points, enabling high‑quality reconstruction of fine local geometry in incomplete point clouds and outperforming prior methods on both dense and sparse benchmarks.

3D visionDeep LearningSkip-Transformer

0 likes · 11 min read

How SnowflakeNet Revolutionizes Point Cloud Completion with Skip‑Transformer

Kuaishou Tech

Sep 17, 2021 · Artificial Intelligence

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

SnowflakeNet introduces a novel Snowflake Point Deconvolution architecture combined with a Skip-Transformer to progressively split seed points, enabling high‑quality point‑cloud completion that preserves fine‑grained geometric details such as smooth surfaces, sharp edges, and corners across dense and sparse datasets.

3D reconstructionDeep LearningSnowflakeNet

0 likes · 10 min read

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

Kuaishou Tech

Jun 21, 2021 · Artificial Intelligence

Kuaishou’s CVPR 2021 Paper Highlights: 3D Vision, Domain Adaptation, Point Cloud Completion, Video Segmentation, and Face Forgery Detection

Kuaishou secured 14 accepted papers at CVPR 2021, spanning 3D hand mesh recovery, unsupervised keypoint detection, point cloud completion, modular interactive video segmentation, deep video matting, co‑salient object detection, occlusion‑aware instance segmentation, semantic image matting, and face forgery detection, showcasing the maturity of its research collaborations.

3D reconstructionCVPRFace Forgery Detection

0 likes · 14 min read

Kuaishou’s CVPR 2021 Paper Highlights: 3D Vision, Domain Adaptation, Point Cloud Completion, Video Segmentation, and Face Forgery Detection