Papers point cloud video understanding
“point cloud video understanding” 태그가 달린 논문 8편 · 필터 해제
Adapting Pre-trained 3D Models for Point Cloud Video Understanding via Cross-frame Spatio-temporal Perception
Point cloud video understanding is becoming increasingly important in fields such as robotics, autonomous driving, and augmented reality, as they can accurately represent object motion and environmental changes. Desp…
Autonomous DrivingGesture Recognitionpoint cloud video understandingSelf-Supervised Learning+1Mamba4D: Efficient 4D Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
Point cloud videos can faithfully capture real-world spatial geometries and temporal dynamics, which are essential for enabling intelligent agents to understand the dynamically changing world. However, designing an e…
Action RecognitionAction SegmentationGPUMamba+4MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
Point cloud videos can faithfully capture real-world spatial geometries and temporal dynamics, which are essential for enabling intelligent agents to understand the dynamically changing world. However, designing an effec…
Action RecognitionAction SegmentationGPUMamba+5A Unified Framework for Human-centric Point Cloud Video Understanding
Human-centric Point Cloud Video Understanding (PVU) is an emerging field focused on extracting and interpreting human-related features from sequences of human point clouds, further advancing downstream human-centric task…
3D Pose EstimationAction RecognitionPoint Cloud Pre-trainingPoint Cloud Rrepresentation Learning+3CrossVideo: Self-supervised Cross-modal Contrastive Learning for Point Cloud Video Understanding
This paper introduces a novel approach named CrossVideo, which aims to enhance self-supervised cross-modal contrastive learning in the field of point cloud video understanding. Traditional supervised learning methods enc…
Contrastive Learningpoint cloud video understandingSelf-Supervised LearningVideo UnderstandingX4D-SceneFormer: Enhanced Scene Understanding on 4D Point Cloud Videos through Cross-modal Knowledge Transfer
The field of 4D point cloud understanding is rapidly developing with the goal of analyzing dynamic 3D point cloud sequences. However, it remains a challenging task due to the sparsity and lack of texture in point clouds.…
Action RecognitionAction Segmentationpoint cloud video understandingScene Understanding+4Masked Spatio-Temporal Structure Prediction for Self-supervised Learning on Point Cloud Videos
Recently, the community has made tremendous progress in developing effective methods for point cloud video understanding that learn from massive amounts of labeled data. However, annotating point cloud videos is usually …
point cloud video understandingSelf-Supervised LearningVideo UnderstandingPoint Primitive Transformer for Long-Term 4D Point Cloud Video Understanding
This paper proposes a 4D backbone for long-term point cloud video understanding. A typical way to capture spatial-temporal context is using 4Dconv or transformer without hierarchy. However, those methods are neither effe…
point cloud video understandingVideo Understanding