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Found 8 papers, 0 papers with code
ONeRF: Unsupervised 3D Object Segmentation from Multiple Views
We present ONeRF, a method that automatically segments and reconstructs object instances in 3D from multi-view RGB images without any additional manual annotations.
NeRF-RPN: A general framework for object detection in NeRFs
Given a pre-trained NeRF model, NeRF-RPN aims to detect all bounding boxes of objects in a scene.
A Grey-box Launch-profile Aware Model for C+L Band Raman Amplification
Based on the physical features of Raman amplification, we propose a three-step modelling scheme based on neural networks (NN) and linear regression.
Physics-informed EDFA Gain Model Based on Active Learning
We propose a physics-informed EDFA gain model based on the active learning method.
Learning Visual Styles from Audio-Visual Associations
Our model learns to manipulate the texture of a scene to match a sound, a problem we term audio-driven image stylization.
Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension
We present Native Chinese Reader (NCR), a new machine reading comprehension (MRC) dataset with particularly long articles in both modern and classical Chinese.
Modality Laziness: Everybody's Business is Nobody's Business
We name this problem of multi-modal training, \emph{Modality Laziness}.
Improving Multi-Modal Learning with Uni-Modal Teachers
We name this problem Modality Failure, and hypothesize that the imbalance of modalities and the implicit bias of common objectives in fusion method prevent encoders of each modality from sufficient feature learning.
Ranked #31 on
Semantic Segmentation
on NYU Depth v2
