2 citations · 3 across the 4 of their papers we have counts for
4 papers
VP-LLM: Text-Driven 3D Volume Completion with Large Language Models through Patchification
Jianmeng Liu, Yichen Liu, Yuyao Zhang +3
Recent conditional 3D completion works have mainly relied on CLIP or BERT to encode textual information, which cannot support complex instruction. Meanwhile, large language models…
SANeRF-HQ: Segment Anything for NeRF in High Quality
Yichen Liu, Benran Hu, Chi-Keung Tang +1
Recently, the Segment Anything Model (SAM) has showcased remarkable capabilities of zero-shot segmentation, while NeRF (Neural Radiance Fields) has gained popularity as a method fo…
Instance Neural Radiance Field
Yichen Liu, Benran Hu, Junkai Huang +2
This paper presents one of the first learning-based NeRF 3D instance segmentation pipelines, dubbed as Instance Neural Radiance Field, or Instance NeRF. Taking a NeRF pretrained fr…
ONeRF: Unsupervised 3D Object Segmentation from Multiple Views
Shengnan Liang, Yichen Liu, Shangzhe Wu +2
We present ONeRF, a method that automatically segments and reconstructs object instances in 3D from multi-view RGB images without any additional manual annotations. The segmented 3…