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Found 4 papers, 1 papers with code
3D Semantic Scene Completion from a Single Depth Image using Adversarial Training
We address the task of 3D semantic scene completion, i. e. , given a single depth image, we predict the semantic labels and occupancy of voxels in a 3D grid representing the scene.
SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences
Despite the relevance of semantic scene understanding for this application, there is a lack of a large dataset for this task which is based on an automotive LiDAR.
Ranked #32 on
3D Semantic Segmentation
on SemanticKITTI
Two Stream 3D Semantic Scene Completion
In this work, we propose a two stream approach that leverages depth information and semantic information, which is inferred from the RGB image, for this task.
Ranked #7 on
3D Semantic Scene Completion
on SemanticKITTI
3D Semantic Scene Completion
Vocal Bursts Valence Prediction
Pose for Action - Action for Pose
In this work we propose to utilize information about human actions to improve pose estimation in monocular videos.
Ranked #5 on
Pose Estimation
on UPenn Action
