46 citations · 83 across the 14 of their papers we have counts for
6 papers · 1 filter
Transferability of Representations Learned using Supervised Contrastive Learning Trained on a Multi-Domain Dataset
Alvin De Jun Tan, Clement Tan, Chai Kiat Yeo
Contrastive learning has shown to learn better quality representations than models trained using cross-entropy loss. They also transfer better to downstream datasets from different…
DeformToon3D: Deformable 3D Toonification from Neural Radiance Fields
Junzhe Zhang, Yushi Lan, Shuai Yang +5
In this paper, we address the challenging problem of 3D toonification, which involves transferring the style of an artistic domain onto a target 3D face with stylized geometry and…
Inferring Past Human Actions in Homes with Abductive Reasoning
Clement Tan, Chai Kiat Yeo, Cheston Tan +1
Abductive reasoning aims to make the most likely inference for a given set of incomplete observations. In this paper, we introduce "Abductive Past Action Inference", a novel resear…
Monocular 3D Object Reconstruction with GAN Inversion
Junzhe Zhang, Daxuan Ren, Zhongang Cai +3
Recovering a textured 3D mesh from a monocular image is highly challenging, particularly for in-the-wild objects that lack 3D ground truths. In this work, we present MeshInversion,…
Unsupervised 3D Shape Completion through GAN Inversion
Junzhe Zhang, Xinyi Chen, Zhongang Cai +6
Most 3D shape completion approaches rely heavily on partial-complete shape pairs and learn in a fully supervised manner. Despite their impressive performances on in-domain data, wh…
MessyTable: Instance Association in Multiple Camera Views
Zhongang Cai, Junzhe Zhang, Daxuan Ren +5
We present an interesting and challenging dataset that features a large number of scenes with messy tables captured from multiple camera views. Each scene in this dataset is highly…