activity
20222025
most citedContrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining

31 citations · 34 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2025

SoFar: Language-Grounded Orientation Bridges Spatial Reasoning and Object Manipulation

Zekun Qi, Wenyao Zhang, Yufei Ding +15

While spatial reasoning has made progress in object localization relationships, it often overlooks object orientation-a key factor in 6-DoF fine-grained manipulation. Traditional p…

cs.CV2024

Learning from Pattern Completion: Self-supervised Controllable Generation

Zhiqiang Chen, Guofan Fan, Jinying Gao +4

The human brain exhibits a strong ability to spontaneously associate different visual attributes of the same or similar visual scene, such as associating sketches and graffiti with…

cs.CV2023★ 2 cited

Point-GCC: Universal Self-supervised 3D Scene Pre-training via Geometry-Color Contrast

Guofan Fan, Zekun Qi, Wenkai Shi +1

Geometry and color information provided by the point clouds are both crucial for 3D scene understanding. Two pieces of information characterize the different aspects of point cloud…

cs.CV2023★ 31 cited

Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining

Zekun Qi, Runpei Dong, Guofan Fan +4

Mainstream 3D representation learning approaches are built upon contrastive or generative modeling pretext tasks, where great improvements in performance on various downstream task…

cs.CV2022★ 1 cited

Language-Assisted 3D Feature Learning for Semantic Scene Understanding

Junbo Zhang, Guofan Fan, Guanghan Wang +3

Learning descriptive 3D features is crucial for understanding 3D scenes with diverse objects and complex structures. However, it is usually unknown whether important geometric attr…