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Found 21 papers, 3 papers with code
Globally Optimal and Efficient Vanishing Point Estimation in Atlanta World
In Atlanta world, given a set of image lines, we aim to cluster them by the unknown-but-sought VPs whose number is unknown.
VPOcc: Exploiting Vanishing Point for Monocular 3D Semantic Occupancy Prediction
First, in the VPZoomer module, we initially utilize VP in feature extraction to achieve information balanced feature extraction across the scene by generating a zoom-in image based on VP.
DITTO: Dual and Integrated Latent Topologies for Implicit 3D Reconstruction
Concretely, DITTO consists of dual latent encoder and integrated implicit decoder.
AiSDF: Structure-aware Neural Signed Distance Fields in Indoor Scenes
Indoor scenes we are living in are visually homogenous or textureless, while they inherently have structural forms and provide enough structural priors for 3D scene reconstruction.
ContactGen: Contact-Guided Interactive 3D Human Generation for Partners
Among various interactions between humans, such as eye contact and gestures, physical interactions by contact can act as an essential moment in understanding human behaviors.
FishRecGAN: An End to End GAN Based Network for Fisheye Rectification and Calibration
We propose an end-to-end deep learning approach to rectify fisheye images and simultaneously calibrate camera intrinsic and distortion parameters.
SlaBins: Fisheye Depth Estimation using Slanted Bins on Road Environments
Based on the slanted MCI, we estimate a set of adaptive bins and a per-pixel probability map for depth estimation.
Diffusion-Based Signed Distance Fields for 3D Shape Generation
In the first stage, a diffusion-based generative model generates a low-resolution SDF of 3D shapes.
Unified 3D Mesh Recovery of Humans and Animals by Learning Animal Exercise
To make the unstable disjoint multi-task learning jointly trainable, we propose to exploit the morphological similarity between humans and animals, motivated by animal exercise where humans imitate animal poses.
Volumetric Propagation Network: Stereo-LiDAR Fusion for Long-Range Depth Estimation
The key idea of our network is to exploit sparse and accurate point clouds as a cue for guiding correspondences of stereo images in a unified 3D volume space.
Stereo Object Matching Network
This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information.
Learning Icosahedral Spherical Probability Map Based on Bingham Mixture Model for Vanishing Point Estimation
Based on this map, we can detect all the VPs.
Non-Local Spatial Propagation Network for Depth Completion
In this paper, we propose a robust and efficient end-to-end non-local spatial propagation network for depth completion.
Ranked #1 on
Depth Completion
on NYU-Depth V2
Globally Optimal Inlier Set Maximization for Atlanta Frame Estimation
In this work, we describe man-made structures via an appropriate structure assumption, called Atlanta world, which contains a vertical direction (typically the gravity direction) and a set of horizontal directions orthogonal to the vertical direction.
Efficient adaptive non-maximal suppression algorithms for homogeneous spatial keypoint distribution
Keypoint detection usually results in a large number of keypoints which are mostly clustered, redundant, and noisy.
Personalized Cinemagraphs using Semantic Understanding and Collaborative Learning
Cinemagraphs are a compelling way to convey dynamic aspects of a scene.
Globally Optimal Manhattan Frame Estimation in Real-Time
Given a set of surface normals, we pose a Manhattan Frame (MF) estimation problem as a consensus set maximization that maximizes the number of inliers over the rotation search space.
Robust and Globally Optimal Manhattan Frame Estimation in Near Real Time
Most man-made environments, such as urban and indoor scenes, consist of a set of parallel and orthogonal planar structures.
Accurate Camera Calibration Robust to Defocus Using a Smartphone
We propose a novel camera calibration method for defocused images using a smartphone under the assumption that the defocus blur is modeled as a convolution of a sharp image with a Gaussian point spread function (PSF).
High Quality Structure From Small Motion for Rolling Shutter Cameras
To address these problems, we introduce a novel 3D reconstruction method from narrow-baseline image sequences that effectively handles the effects of a rolling shutter that occur from most of commercial digital cameras.
Vision System and Depth Processing for DRC-HUBO+
This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015.
