7 citations · 24 across the 10 of their papers we have counts for
10 papers
CVT-xRF: Contrastive In-Voxel Transformer for 3D Consistent Radiance Fields from Sparse Inputs
Yingji Zhong, Lanqing Hong, Zhenguo Li +1
Neural Radiance Fields (NeRF) have shown impressive capabilities for photorealistic novel view synthesis when trained on dense inputs. However, when trained on sparse inputs, NeRF…
DetDiffusion: Synergizing Generative and Perceptive Models for Enhanced Data Generation and Perception
Yibo Wang, Ruiyuan Gao, Kai Chen +8
Current perceptive models heavily depend on resource-intensive datasets, prompting the need for innovative solutions. Leveraging recent advances in diffusion models, synthetic data…
Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts
Zhili Liu, Kai Chen, Jianhua Han +4
Masked Autoencoder~(MAE) is a prevailing self-supervised learning method that achieves promising results in model pre-training. However, when the various downstream tasks have data…
G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object Detection
Fan Wu, Jinling Gao, Lanqing Hong +3
In this paper, we focus on a realistic yet challenging task, Single Domain Generalization Object Detection (S-DGOD), where only one source domain's data can be used for training ob…
DiffGuard: Semantic Mismatch-Guided Out-of-Distribution Detection using Pre-trained Diffusion Models
Ruiyuan Gao, Chenchen Zhao, Lanqing Hong +1
Given a classifier, the inherent property of semantic Out-of-Distribution (OOD) samples is that their contents differ from all legal classes in terms of semantics, namely semantic…
ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis
Shoukang Hu, Kaichen Zhou, Kaiyu Li +6
Neural Radiance Fields (NeRF) has demonstrated remarkable 3D reconstruction capabilities with dense view images. However, its performance significantly deteriorates under sparse vi…