Image-based 3D object reconstruction: State-of-the-art and trends in the deep learning era
3D reconstruction is a longstanding ill-posed problem, which has been explored for decades
by the computer vision, computer graphics, and machine learning communities. Since 2015 …
by the computer vision, computer graphics, and machine learning communities. Since 2015 …
Total3dunderstanding: Joint layout, object pose and mesh reconstruction for indoor scenes from a single image
Semantic reconstruction of indoor scenes refers to both scene understanding and object
reconstruction. Existing works either address one part of this problem or focus on …
reconstruction. Existing works either address one part of this problem or focus on …
Lassie: Learning articulated shapes from sparse image ensemble via 3d part discovery
Creating high-quality articulated 3D models of animals is challenging either via manual
creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D …
creation or using 3D scanning tools. Therefore, techniques to reconstruct articulated 3D …
Pq-net: A generative part seq2seq network for 3d shapes
We introduce PQ-NET, a deep neural network which represents and generates 3D shapes
via sequential part assembly. The input to our network is a 3D shape segmented into parts …
via sequential part assembly. The input to our network is a 3D shape segmented into parts …
No-reference point cloud quality assessment via domain adaptation
We present a novel no-reference quality assessment metric, the image transferred point
cloud quality assessment (IT-PCQA), for 3D point clouds. For quality assessment, deep …
cloud quality assessment (IT-PCQA), for 3D point clouds. For quality assessment, deep …
Lepard: Learning explicit part discovery for 3d articulated shape reconstruction
Reconstructing the 3D articulated shape of an animal from a single in-the-wild image is a
challenging task. We propose LEPARD, a learning-based framework that discovers …
challenging task. We propose LEPARD, a learning-based framework that discovers …
Hi-lassie: High-fidelity articulated shape and skeleton discovery from sparse image ensemble
Automatically estimating 3D skeleton, shape, camera viewpoints, and part articulation from
sparse in-the-wild image ensembles is a severely under-constrained and challenging …
sparse in-the-wild image ensembles is a severely under-constrained and challenging …
Dense 3d point cloud reconstruction using a deep pyramid network
P Mandikal, VB Radhakrishnan - 2019 IEEE Winter Conference …, 2019 - ieeexplore.ieee.org
Reconstructing a high-resolution 3D model of an object is a challenging task in computer
vision. Designing scalable and light-weight architectures is crucial while addressing this …
vision. Designing scalable and light-weight architectures is crucial while addressing this …
Towards high-fidelity single-view holistic reconstruction of indoor scenes
We present a new framework to reconstruct holistic 3D indoor scenes including both room
background and indoor objects from single-view images. Existing methods can only produce …
background and indoor objects from single-view images. Existing methods can only produce …
C2FNet: A coarse-to-fine network for multi-view 3D point cloud generation
Generation of a 3D model of an object from multiple views has a wide range of applications.
Different parts of an object would be accurately captured by a particular view or a subset of …
Different parts of an object would be accurately captured by a particular view or a subset of …