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20152026
most citedNeural 3D Reconstruction in the Wild

105 citations · 625 across the 101 of their papers we have counts for

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Showing 2022Show all

13 papers · 1 filter

cs.CV2022

Reconstructing Hand-Held Objects from Monocular Video

Di Huang, Xiaopeng Ji, Xingyi He +5

This paper presents an approach that reconstructs a hand-held object from a monocular video. In contrast to many recent methods that directly predict object geometry by a trained n…

cs.LG2022

LADDER: Latent Boundary-guided Adversarial Training

Xiaowei Zhou, Ivor W. Tsang, Jie Yin

Deep Neural Networks (DNNs) have recently achieved great success in many classification tasks. Unfortunately, they are vulnerable to adversarial attacks that generate adversarial e…

cs.CV2022★ 1 cited

PlanarRecon: Real-time 3D Plane Detection and Reconstruction from Posed Monocular Videos

Yiming Xie, Matheus Gadelha, Fengting Yang +2

We present PlanarRecon -- a novel framework for globally coherent detection and reconstruction of 3D planes from a posed monocular video. Unlike previous works that detect planes i…

cs.CV2022★ 105 cited

Neural 3D Reconstruction in the Wild

Jiaming Sun, Xi Chen, Qianqian Wang +4

We are witnessing an explosion of neural implicit representations in computer vision and graphics. Their applicability has recently expanded beyond tasks such as shape generation a…

cs.CV2022

OnePose: One-Shot Object Pose Estimation without CAD Models

Jiaming Sun, Zihao Wang, Siyu Zhang +4

We propose a new method named OnePose for object pose estimation. Unlike existing instance-level or category-level methods, OnePose does not rely on CAD models and can handle objec…

cs.CV2022★ 4 cited

Neural 3D Scene Reconstruction with the Manhattan-world Assumption

Haoyu Guo, Sida Peng, Haotong Lin +4

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results on textured objects,…