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Knowledge of 3-D object shape is of great importance to robot manipulation tasks, but may not be readily available in unstructured environments. While vision is often occluded during robot-object interaction, high-resolution tactile sensors…

Robotics · Computer Science 2022-03-11 Sudharshan Suresh , Zilin Si , Joshua G. Mangelson , Wenzhen Yuan , Michael Kaess

The ability to estimate the 3D human shape and pose from images can be useful in many contexts. Recent approaches have explored using graph convolutional networks and achieved promising results. The fact that the 3D shape is represented by…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Xin Yu , Jeroen van Baar , Siheng Chen

3D Morphable Model (3DMM) fitting has widely benefited face analysis due to its strong 3D priori. However, previous reconstructed 3D faces suffer from degraded visual verisimilitude due to the loss of fine-grained geometry, which is…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Xiangyu Zhu , Chang Yu , Di Huang , Zhen Lei , Hao Wang , Stan Z. Li

Automatic anomaly detection based on visual cues holds practical significance in various domains, such as manufacturing and product quality assessment. This paper introduces a new conditional anomaly detection problem, which involves…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Ankan Bhunia , Changjian Li , Hakan Bilen

Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as…

Computer Vision and Pattern Recognition · Computer Science 2017-03-07 Leonid Pishchulin , Stefanie Wuhrer , Thomas Helten , Christian Theobalt , Bernt Schiele

Neural implicit functions have achieved impressive results for reconstructing 3D shapes from single images. However, the image features for describing 3D point samplings of implicit functions are less effective when significant variations…

Computer Vision and Pattern Recognition · Computer Science 2022-02-01 Yixin Zhuang , Yunzhe Liu , Yujie Wang , Baoquan Chen

While methods that regress 3D human meshes from images have progressed rapidly, the estimated body shapes often do not capture the true human shape. This is problematic since, for many applications, accurate body shape is as important as…

Computer Vision and Pattern Recognition · Computer Science 2022-06-15 Vasileios Choutas , Lea Muller , Chun-Hao P. Huang , Siyu Tang , Dimitrios Tzionas , Michael J. Black

We propose a method for 3D object reconstruction and 6D-pose estimation from 2D images that uses knowledge about object shape as the primary key. In the proposed pipeline, recognition and labeling of objects in 2D images deliver 2D segment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Marcell Wolnitza , Osman Kaya , Tomas Kulvicius , Florentin Wörgötter , Babette Dellen

3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses. This is because the uncertainty of the estimated 2D landmarks will affect the quality of face reconstruction. In…

Computer Vision and Pattern Recognition · Computer Science 2020-09-15 Kun Li , Jing Yang , Nianhong Jiao , Jinsong Zhang , Yu-Kun Lai

We present ShapeClipper, a novel method that reconstructs 3D object shapes from real-world single-view RGB images. Instead of relying on laborious 3D, multi-view or camera pose annotation, ShapeClipper learns shape reconstruction from a set…

Computer Vision and Pattern Recognition · Computer Science 2023-04-14 Zixuan Huang , Varun Jampani , Anh Thai , Yuanzhen Li , Stefan Stojanov , James M. Rehg

This paper addresses the problem of 3D human pose and shape estimation from a single image. Previous approaches consider a parametric model of the human body, SMPL, and attempt to regress the model parameters that give rise to a mesh…

Computer Vision and Pattern Recognition · Computer Science 2019-05-09 Nikos Kolotouros , Georgios Pavlakos , Kostas Daniilidis

From a single image, humans are able to perceive the full 3D shape of an object by exploiting learned shape priors from everyday life. Contemporary single-image 3D reconstruction algorithms aim to solve this task in a similar fashion, but…

Computer Vision and Pattern Recognition · Computer Science 2018-12-31 Xiuming Zhang , Zhoutong Zhang , Chengkai Zhang , Joshua B. Tenenbaum , William T. Freeman , Jiajun Wu

We present Implicit-Scale 3D Reconstruction from Monocular Multi-Food Images, a benchmark dataset designed to advance geometry-based food portion estimation in realistic dining scenarios. Existing dietary assessment methods largely rely on…

Computer Vision and Pattern Recognition · Computer Science 2026-02-16 Yuhao Chen , Gautham Vinod , Siddeshwar Raghavan , Talha Ibn Mahmud , Bruce Coburn , Jinge Ma , Fengqing Zhu , Jiangpeng He

We aim to infer 3D shape and pose of object from a single image and propose a learning-based approach that can train from unstructured image collections, supervised by only segmentation outputs from off-the-shelf recognition systems (i.e.…

Computer Vision and Pattern Recognition · Computer Science 2021-02-12 Yufei Ye , Shubham Tulsiani , Abhinav Gupta

Estimation of 3D human pose from monocular image has gained considerable attention, as a key step to several human-centric applications. However, generalizability of human pose estimation models developed using supervision on large-scale…

Computer Vision and Pattern Recognition · Computer Science 2020-06-26 Jogendra Nath Kundu , Siddharth Seth , Rahul M , Mugalodi Rakesh , R. Venkatesh Babu , Anirban Chakraborty

Human face is a 3D object with shape and surface texture. 3D Morphable Model (3DMM) is a powerful tool for reconstructing the 3D face from a single 2D face image. In the shape fitting process, 3DMM estimates the correspondence between 2D…

Computer Vision and Pattern Recognition · Computer Science 2018-08-17 Yu Yanga , Xiao-Jun Wu , Josef Kittler

Animals are diverse in shape, but building a deformable shape model for a new species is not always possible due to the lack of 3D data. We present a method to capture new species using an articulated template and images of that species. In…

Computer Vision and Pattern Recognition · Computer Science 2021-05-21 Yufu Wang , Nikos Kolotouros , Kostas Daniilidis , Marc Badger

Reasoning 3D shapes from 2D images is an essential yet challenging task, especially when only single-view images are at our disposal. While an object can have a complicated shape, individual parts are usually close to geometric primitives…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Chun-Han Yao , Wei-Chih Hung , Varun Jampani , Ming-Hsuan Yang

We address the problem of estimating human pose and body shape from 3D scans over time. Reliable estimation of 3D body shape is necessary for many applications including virtual try-on, health monitoring, and avatar creation for virtual…

Computer Vision and Pattern Recognition · Computer Science 2017-04-20 Chao Zhang , Sergi Pujades , Michael Black , Gerard Pons-Moll

Feedforward monocular face capture methods seek to reconstruct posed faces from a single image of a person. Current state of the art approaches have the ability to regress parametric 3D face models in real-time across a wide range of…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Kelian Baert , Shrisha Bharadwaj , Fabien Castan , Benoit Maujean , Marc Christie , Victoria Abrevaya , Adnane Boukhayma