5 citations · 7 across the 5 of their papers we have counts for
5 papers
X-LRM: X-ray Large Reconstruction Model for Extremely Sparse-View Computed Tomography Recovery in One Second
Guofeng Zhang, Ruyi Zha, Hao He +4
Sparse-view 3D CT reconstruction aims to recover volumetric structures from a limited number of 2D X-ray projections. Existing feedforward methods are constrained by the scarcity o…
SEGT: A General Spatial Expansion Group Transformer for nuScenes Lidar-based Object Detection Task
Cheng Mei, Hao He, Yahui Liu +1
In the technical report, we present a novel transformer-based framework for nuScenes lidar-based object detection task, termed Spatial Expansion Group Transformer (SEGT). To effici…
LucidFusion: Reconstructing 3D Gaussians with Arbitrary Unposed Images
Hao He, Yixun Liang, Luozhou Wang +5
Recent large reconstruction models have made notable progress in generating high-quality 3D objects from single images. However, current reconstruction methods often rely on explic…
View-Consistent Hierarchical 3D Segmentation Using Ultrametric Feature Fields
Haodi He, Colton Stearns, Adam W. Harley +1
Large-scale vision foundation models such as Segment Anything (SAM) demonstrate impressive performance in zero-shot image segmentation at multiple levels of granularity. However, t…
Uncovering Prototypical Knowledge for Weakly Open-Vocabulary Semantic Segmentation
Fei Zhang, Tianfei Zhou, Boyang Li +6
This paper studies the problem of weakly open-vocabulary semantic segmentation (WOVSS), which learns to segment objects of arbitrary classes using mere image-text pairs. Existing w…