Zanuncio, J.C.[Jose Cola]
Co Author Listing * Remote Sensing to Detect Nests of the Leaf-Cutting Ant Atta sexdens (Hymenoptera: Formicidae) in Teak Plantations
Includes: Zanuncio, J.C.[Jose Cola] Zanuncio, J.C.[José Cola]
Zanutta, A.[Antonio]
Co Author Listing * Multi-Temporal Investigation of the Boulder Clay Glacier and Northern Foothills (Victoria Land, Antarctica) by Integrated Surveying Techniques
* New Geodetic and Gravimetric Maps to Infer Geodynamics of Antarctica with Insights on Victoria Land
* Sea Tide Influence on Ice Flow of David Drygalski's Ice Tongue Inferred from Geodetic GNSS Observations and SAR Offset Tracking Analysis
* Victoria Land, Antarctica: An Improved Geodynamic Interpretation Based on the Strain Rate Field of the Current Crustal Motion and Moho Depth Model
Zanuttigh, P.[Pietro]
Co Author Listing * 3D Imaging Techniques and Multimedia Applications: Guest editor's introduction
* Asynchronous Federated Continual Learning
* Combination of Spatially-Modulated ToF and Structured Light for MPI-Free Depth Estimation
* Combining color and shape descriptors for 3D model retrieval
* Combining multiple depth-based descriptors for hand gesture recognition
* Compression of depth information for 3D rendering
* Continual coarse-to-fine domain adaptation in semantic segmentation
* Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
* Deep learning for 3D shape classification from multiple depth maps
* Deep Learning for Confidence Information in Stereo and ToF Data Fusion
* Deep Learning for Multi-path Error Removal in ToF Sensors
* Depth map coding with elastic contours and 3D surface prediction
* Distortion-Sensitive Synthesis of Texture and Geometry in Interactive 3D Visualization
* Edge-Aware Graph Matching Network for Part-Based Semantic Segmentation
* Gmnet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild
* Greedy Non-Linear Approximation of the Plenoptic Function for Interactive Transmission of 3D Scenes
* Hand gesture recognition with leap motion and kinect devices
* Incremental Learning Techniques for Semantic Segmentation
* joint multi-view plus depth image coding scheme based on 3D-warping, A
* Joint segmentation of color and depth data based on splitting and merging driven by surface fitting
* Knowledge distillation for incremental learning in semantic segmentation
* Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
* Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning
* Locally Consistent ToF and Stereo Data Fusion
* Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Maps, A
* novel framework for the interactive transmission of 3D scenes, A
* novel multi-view image coding scheme based on view-warping and 3D-DCT, A
* Pairwise similarities for scene segmentation combining color and depth data
* Probabilistic Approach to ToF and Stereo Data Fusion, A
* Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixels Measurement Models
* Rate Distortion Framework for 3D Browsing, A
* RECALL: Replay-based Continual Learning in Semantic Segmentation
* Reliable Fusion of ToF and Stereo Depth Driven by Confidence Measures
* Scalable Coding of Depth Maps With R-D Optimized Embedding
* Scene Segmentation Assisted by Stereo Vision
* Scene Segmentation Driven by Deep Learning and Surface Fitting
* Scene segmentation from depth and color data driven by surface fitting
* Segmentation and semantic labelling of RGBD data with convolutional neural networks and surface fitting
* SELMA: SEmantic Large-Scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints
* Semi-supervised Deep Learning Techniques for Spectrum Reconstruction
* Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers
* SynDrone: Multi-modal UAV Dataset for Urban Scenarios
* Time-of-Flight Cameras and Microsoft Kinect™
* Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment
* Unsupervised Domain Adaptation for ToF Data Denoising With Adversarial Learning
* Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings
* Unsupervised Domain Adaptation of Deep Networks for ToF Depth Refinement
* Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training
Includes: Zanuttigh, P.[Pietro] Zanuttigh, P.
48 for Zanuttigh, P.