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cs.CV2026

Cross4D-JEPA: Dense Cross-modal Correspondence Distillation for 4D Point Cloud Representation Learning

Trung Thanh Nguyen, Hai Nguyen-Truong, Tu Vo +2

Automatic understanding of dynamic 4D point clouds, the 3D-point sequences captured over time by depth sensors and LiDAR, is central to robotics and embodied perception. Yet annota…

cs.CV2026

SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds

Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding +10

Instance segmentation of trees in forest LiDAR point clouds is constrained by label scarcity: A single hectare holds millions of points and hundreds of overlapping tree crowns, mak…

cs.CV2026

ForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation

Trung Thanh Nguyen, Tuan-Anh Vu, Duc Viet Le +4

Semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the complex 3D structure of forests into acti…

cs.CV2025

DePT3R: Joint Dense Point Tracking and 3D Reconstruction of Dynamic Scenes in a Single Forward Pass

Vivek Alumootil, Tuan-Anh Vu

Current methods for dense 3D point tracking in dynamic scenes typically rely on pairwise processing, require known camera poses, or assume temporal ordering of input frames, thereb…

cs.CV2025

HiddenObject: Modality-Agnostic Fusion for Multimodal Hidden Object Detection

Harris Song, Tuan-Anh Vu, Sanjith Menon +2

Detecting hidden or partially concealed objects remains a fundamental challenge in multimodal environments, where factors like occlusion, camouflage, and lighting variations signif…

cs.CV2025

Reconstruction Using the Invisible: Intuition from NIR and Metadata for Enhanced 3D Gaussian Splatting

Gyusam Chang, Tuan-Anh Vu, Vivek Alumootil +4

While 3D Gaussian Splatting (3DGS) has rapidly advanced, its application in agriculture remains underexplored. Agricultural scenes present unique challenges for 3D reconstruction m…