Segment any point cloud sequences by distilling vision foundation models
Recent advancements in vision foundation models (VFMs) have opened up new
possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a …
possibilities for versatile and efficient visual perception. In this work, we introduce Seal, a …
An outlook into the future of egocentric vision
What will the future be? We wonder! In this survey, we explore the gap between current
research in egocentric vision and the ever-anticipated future, where wearable computing …
research in egocentric vision and the ever-anticipated future, where wearable computing …
LeaF: Learning Frames for 4D Point Cloud Sequence Understanding
We focus on learning descriptive geometry and motion features from 4D point cloud
sequences in this work. Existing works usually develop generic 4D learning tools without …
sequences in this work. Existing works usually develop generic 4D learning tools without …
Masked 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 …
for point cloud video understanding that learn from massive amounts of labeled data …
Point contrastive prediction with semantic clustering for self-supervised learning on point cloud videos
We propose a unified point cloud video self-supervised learning framework for object-centric
and scene-centric data. Previous methods commonly conduct representation learning at the …
and scene-centric data. Previous methods commonly conduct representation learning at the …
A Unified Framework for Human-centric Point Cloud Video Understanding
Abstract Human-centric Point Cloud Video Understanding (PVU) is an emerging field
focused on extracting and interpreting human-related features from sequences of human …
focused on extracting and interpreting human-related features from sequences of human …
CrossVideo: 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 …
supervised cross-modal contrastive learning in the field of point cloud video understanding …
X4d-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 …
dynamic 3D point cloud sequences. However, it remains a challenging task due to the …
MAMBA4D: Efficient Long-Sequence Point Cloud Video Understanding with Disentangled Spatial-Temporal State Space Models
Point cloud videos effectively capture real-world spatial geometries and temporal dynamics,
which are essential for enabling intelligent agents to understand the dynamically changing …
which are essential for enabling intelligent agents to understand the dynamically changing …
A review of point cloud segmentation for understanding 3D indoor scenes
Y Sun, X Zhang, Y Miao - Visual Intelligence, 2024 - Springer
Point cloud segmentation is an essential task in three-dimensional (3D) vision and
intelligence. It is a critical step in understanding 3D scenes with a variety of applications …
intelligence. It is a critical step in understanding 3D scenes with a variety of applications …