… We introduce an approach for selecting objects in neural volumetric 3D representations,
such as multi-plane images (MPI) and neural radiance fields (NeRF). Our approach takes a set …

… In this paper, we propose NeuralHOFusion, a neural approach for volumetric human-object …
neural implicit modeling and blending advances, where the captured humans and objects …

… feature vector, hence defining the volumetric object representation that we refer to as neural
… We ablate the geometry selection and background features during training. In NOVUM, we …

… the user select the foreground object bounding box in 3D. After reconstruction, neural volumetric
… The shader performs volumetric raycasting, aggregates sample points and produces a …

… In summary, we propose a novel volumetric representation that is object/scene agnostic, …
To maximize coverage, we select a subset of cameras that are roughly orthogonal, although …

… Neural Network (CNNs), several architectures have been proposed for detecting objects in
… shows a sample inventory of selected object instances detected and densely reconstructed …

… The impact of octree depths as evaluated to select the best input depth and multiple
experiments were conducted to select the best orientation on perspective depth. We first selected …

… object capture scheme to provide sufficient motion priors. We further introduce a separated
instant neural … Moreover, we introduce an online key frame selection scheme and a rendering-…

… volumetric rendering function based on these two design principles, improving the state of the
art in volumetric … In particular we select a window of 3 keyframes, the new keyframe and its …

… In real world 3D object contains different rotations, the selection of optimal CNN model for a
… This has been used in combining traditional neural networks [19]. The input to these models …