83 citations · 305 across the 33 of their papers we have counts for
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VPP: Efficient Conditional 3D Generation via Voxel-Point Progressive Representation
Zekun Qi, Muzhou Yu, Runpei Dong +1
Conditional 3D generation is undergoing a significant advancement, enabling the free creation of 3D content from inputs such as text or 2D images. However, previous approaches have…
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…
Revisiting Data Augmentation in Model Compression: An Empirical and Comprehensive Study
Muzhou Yu, Linfeng Zhang, Kaisheng Ma
The excellent performance of deep neural networks is usually accompanied by a large number of parameters and computations, which have limited their usage on the resource-limited ed…
CORSD: Class-Oriented Relational Self Distillation
Muzhou Yu, Sia Huat Tan, Kailu Wu +3
Knowledge distillation conducts an effective model compression method while holding some limitations:(1) the feature based distillation methods only focus on distilling the feature…
CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP
Junbo Zhang, Runpei Dong, Kaisheng Ma
Training a 3D scene understanding model requires complicated human annotations, which are laborious to collect and result in a model only encoding close-set object semantics. In co…
Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs
Yu Duan, Zhongfan Jia, Qian Li +2
Rapidly learning from ongoing experiences and remembering past events with a flexible memory system are two core capacities of biological intelligence. While the underlying neural…
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…