28 citations · 34 across the 7 of their papers we have counts for
7 papers · 1 filter
S3E-GNN: Sparse Spatial Scene Embedding with Graph Neural Networks for Camera Relocalization
Ran Cheng, Xinyu Jiang, Yuan Chen +2
Camera relocalization is the key component of simultaneous localization and mapping (SLAM) systems. This paper proposes a learning-based approach, named Sparse Spatial Scene Embedd…
Semantic-Aware Pretraining for Dense Video Captioning
Teng Wang, Zhu Liu, Feng Zheng +3
This report describes the details of our approach for the event dense-captioning task in ActivityNet Challenge 2021. We present a semantic-aware pretraining method for dense video…
GP-S3Net: Graph-based Panoptic Sparse Semantic Segmentation Network
Ryan Razani, Ran Cheng, Enxu Li +3
Panoptic segmentation as an integrated task of both static environmental understanding and dynamic object identification, has recently begun to receive broad research interest. In…
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Shihua Huang, Zhichao Lu, Ran Cheng +1
Recent advancements in deep neural networks have made remarkable leap-forwards in dense image prediction. However, the issue of feature alignment remains as neglected by most exist…
Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions
Ryan Razani, Ran Cheng, Ehsan Taghavi +1
Autonomous driving vehicles and robotic systems rely on accurate perception of their surroundings. Scene understanding is one of the crucial components of perception modules. Among…
S3Net: 3D LiDAR Sparse Semantic Segmentation Network
Ran Cheng, Ryan Razani, Yuan Ren +1
Semantic Segmentation is a crucial component in the perception systems of many applications, such as robotics and autonomous driving that rely on accurate environmental perception…