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Found 7 papers, 5 papers with code
Free-Editor: Zero-shot Text-driven 3D Scene Editing
To date, editing 3D scenes requires either re-training the model to adapt to various 3D edited scenes or design-specific methods for each special editing type.
LatentEditor: Text Driven Local Editing of 3D Scenes
Our approach achieves faster editing speeds and superior output quality compared to existing 3D editing models, bridging the gap between textual instructions and high-quality 3D scene editing in latent space.
CEFHRI: A Communication Efficient Federated Learning Framework for Recognizing Industrial Human-Robot Interaction
Machine learning plays a vital role in industrial HRI by enhancing the adaptability and autonomy of robots in complex environments.
Coordinate Quantized Neural Implicit Representations for Multi-view Reconstruction
To resolve this issue in a general sense, we introduce to learn neural implicit representations with quantized coordinates, which reduces the uncertainty and ambiguity in the field during optimization.
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model
It can be challenging to identify brain MRI anomalies using supervised deep-learning techniques due to anatomical heterogeneity and the requirement for pixel-level labeling.
VC-Net: Deep Volume-Composition Networks for Segmentation and Visualization of Highly Sparse and Noisy Image Data
A multi-stream convolutional neural network is proposed to learn the 3D volume and 2D MIP features respectively and then explore their inter-dependencies in a joint volume-composition embedding space by unprojecting the MIP features into 3D volume embedding space.
A-CNN: Annularly Convolutional Neural Networks on Point Clouds
Analyzing the geometric and semantic properties of 3D point clouds through the deep networks is still challenging due to the irregularity and sparsity of samplings of their geometric structures.
Ranked #35 on
Semantic Segmentation
on S3DIS
