OBER (OBject-Effect Removal) is a hybrid dataset designed to support research in object removal with effects, combining both camera-captured and simulated data. 🔥 We have released the full dataset ...
Abstract: We propose an interactive approach for 3D instance segmentation, where users can iteratively collaborate with a deep learning model to segment objects directly in a 3D point cloud. Current ...
Abstract: Dual quadrics as landmarks in object-oriented SLAM have recently attracted much attention due to the advantages in the mathematical completeness of projective geometry. Current researches ...
We propose MaskCut approach to generate pseudo-masks for multiple objects in an image. CutLER can learn unsupervised object detectors and instance segmentors solely on ImageNet-1K. CutLER exhibits ...
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