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Found 5 papers, 0 papers with code
Challenging Common Paradigms in Multi-Task Learning
Second, the notion of gradient conflicts has often been phrased as a specific problem in MTL.
Learning-based Relational Object Matching Across Views
Our approach compares favorably to previous state-of-the-art object-level matching approaches and achieves improved performance over a pure keypoint-based approach for large view-point changes.
Weakly Supervised Learning of Multi-Object 3D Scene Decompositions Using Deep Shape Priors
Our approach learns to decompose images of synthetic scenes with multiple objects on a planar surface into its constituent scene objects and to infer their 3D properties from a single view.
Semi-Supervised Learning of Multi-Object 3D Scene Representations
By differentiable rendering, we train our model to decompose scenes self-supervised from RGB-D images.
3D-BEVIS: Bird's-Eye-View Instance Segmentation
A lot of progress was made in the field of object classification and semantic segmentation.
Ranked #4 on
3D Semantic Instance Segmentation
on ScanNetV2
3D Instance Segmentation
3D Semantic Instance Segmentation
+4
