Search Results for author:
Found 5 papers, 3 papers with code
NeRF2Points: Large-Scale Point Cloud Generation From Street Views' Radiance Field Optimization
Neural Radiance Fields (NeRF) have emerged as a paradigm-shifting methodology for the photorealistic rendering of objects and environments, enabling the synthesis of novel viewpoints with remarkable fidelity.
Learning Triangular Distribution in Visual World
Convolution neural network is successful in pervasive vision tasks, including label distribution learning, which usually takes the form of learning an injection from the non-linear visual features to the well-defined labels.
FemtoDet: An Object Detection Baseline for Energy Versus Performance Tradeoffs
Efficient detectors for edge devices are often optimized for parameters or speed count metrics, which remain in weak correlation with the energy of detectors.
Ranked #30 on
Object Detection
on PASCAL VOC 2007
GuidedMix-Net: Semi-supervised Semantic Segmentation by Using Labeled Images as Reference
In this paper, we propose a novel method for semi-supervised semantic segmentation named GuidedMix-Net, by leveraging labeled information to guide the learning of unlabeled instances.
GuidedMix-Net: Learning to Improve Pseudo Masks Using Labeled Images as Reference
To take advantage of the labeled examples and guide unlabeled data learning, we further propose a mask generation module to generate high-quality pseudo masks for the unlabeled data.
