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Found 6 papers, 5 papers with code
FineRecon: Depth-aware Feed-forward Network for Detailed 3D Reconstruction
Recent works on 3D reconstruction from posed images have demonstrated that direct inference of scene-level 3D geometry without test-time optimization is feasible using deep neural networks, showing remarkable promise and high efficiency.
LivePose: Online 3D Reconstruction from Monocular Video with Dynamic Camera Poses
Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates.
Interactive Segmentation and Visualization for Tiny Objects in Multi-megapixel Images
We introduce an interactive image segmentation and visualization framework for identifying, inspecting, and editing tiny objects (just a few pixels wide) in large multi-megapixel high-dynamic-range (HDR) images.
VoRTX: Volumetric 3D Reconstruction With Transformers for Voxelwise View Selection and Fusion
To this end, we introduce VoRTX, an end-to-end volumetric 3D reconstruction network using transformers for wide-baseline, multi-view feature fusion.
3DVNet: Multi-View Depth Prediction and Volumetric Refinement
Furthermore, unlike existing volumetric MVS techniques, our 3D CNN operates on a feature-augmented point cloud, allowing for effective aggregation of multi-view information and flexible iterative refinement of depth maps.
Ranked #5 on
3D Action Recognition
on NTU RGB+D
Sparse Fusion for Multimodal Transformers
Multimodal classification is a core task in human-centric machine learning.
