230 citations · 725 across the 49 of their papers we have counts for
44 papers · 1 filter
ASTRA: Asynchronous Spatio-Temporal Reconstruction via Trajectory Alignment
Junyu Zhu, Hao Zhu, Xinzhuo Zhang +4
Dynamic 3D scene reconstruction has made significant progress with multi-camera systems, often relying on temporally aligned observations across views. However, in real-world scena…
Inverting the Imaging Process by Learning an Implicit Camera Model
Xin Huang, Qi Zhang, Ying Feng +2
Representing visual signals with implicit coordinate-based neural networks, as an effective replacement of the traditional discrete signal representation, has gained considerable p…
WildLight: In-the-wild Inverse Rendering with a Flashlight
Ziang Cheng, Junxuan Li, Hongdong Li
This paper proposes a practical photometric solution for the challenging problem of in-the-wild inverse rendering under unknown ambient lighting. Our system recovers scene geometry…
CircNet: Meshing 3D Point Clouds with Circumcenter Detection
Huan Lei, Ruitao Leng, Liang Zheng +1
Reconstructing 3D point clouds into triangle meshes is a key problem in computational geometry and surface reconstruction. Point cloud triangulation solves this problem by providin…
Rolling Shutter Inversion: Bring Rolling Shutter Images to High Framerate Global Shutter Video
Bin Fan, Yuchao Dai, Hongdong Li
A single rolling-shutter (RS) image may be viewed as a row-wise combination of a sequence of global-shutter (GS) images captured by a (virtual) moving GS camera within the exposure…
CVLNet: Cross-View Semantic Correspondence Learning for Video-based Camera Localization
Yujiao Shi, Xin Yu, Shan Wang +1
This paper tackles the problem of Cross-view Video-based camera Localization (CVL). The task is to localize a query camera by leveraging information from its past observations, i.e…
Self-calibrating Photometric Stereo by Neural Inverse Rendering
Junxuan Li, Hongdong Li
This paper tackles the task of uncalibrated photometric stereo for 3D object reconstruction, where both the object shape, object reflectance, and lighting directions are unknown. T…
CropMix: Sampling a Rich Input Distribution via Multi-Scale Cropping
Junlin Han, Lars Petersson, Hongdong Li +1
We present a simple method, CropMix, for the purpose of producing a rich input distribution from the original dataset distribution. Unlike single random cropping, which may inadver…
Unsupervised Video Interpolation by Learning Multilayered 2.5D Motion Fields
Ziang Cheng, Shihao Jiang, Hongdong Li
The problem of video frame interpolation is to increase the temporal resolution of a low frame-rate video, by interpolating novel frames between existing temporally sparse frames.…
Beyond Cross-view Image Retrieval: Highly Accurate Vehicle Localization Using Satellite Image
Yujiao Shi, Hongdong Li
This paper addresses the problem of vehicle-mounted camera localization by matching a ground-level image with an overhead-view satellite map. Existing methods often treat this prob…
Deep Non-rigid Structure-from-Motion: A Sequence-to-Sequence Translation Perspective
Hui Deng, Tong Zhang, Yuchao Dai +3
Directly regressing the non-rigid shape and camera pose from the individual 2D frame is ill-suited to the Non-Rigid Structure-from-Motion (NRSfM) problem. This frame-by-frame 3D re…
Stereo Unstructured Magnification: Multiple Homography Image for View Synthesis
Qi Zhang, Xin Huang, Ying Feng +3
This paper studies the problem of view synthesis with certain amount of rotations from a pair of images, what we called stereo unstructured magnification. While the multi-plane ima…
Accurate 3-DoF Camera Geo-Localization via Ground-to-Satellite Image Matching
Yujiao Shi, Xin Yu, Liu Liu +3
We address the problem of ground-to-satellite image geo-localization, that is, estimating the camera latitude, longitude and orientation (azimuth angle) by matching a query image c…
Neural Reflectance for Shape Recovery with Shadow Handling
Junxuan Li, Hongdong Li
This paper aims at recovering the shape of a scene with unknown, non-Lambertian, and possibly spatially-varying surface materials. When the shape of the object is highly complex an…
Multi-level Second-order Few-shot Learning
Hongguang Zhang, Hongdong Li, Piotr Koniusz
We propose a Multi-level Second-order (MlSo) few-shot learning network for supervised or unsupervised few-shot image classification and few-shot action recognition. We leverage so-…
You Only Cut Once: Boosting Data Augmentation with a Single Cut
Junlin Han, Pengfei Fang, Weihao Li +5
We present You Only Cut Once (YOCO) for performing data augmentations. YOCO cuts one image into two pieces and performs data augmentations individually within each piece. Applying…
Deep Image Deblurring: A Survey
Kaihao Zhang, Wenqi Ren, Wenhan Luo +4
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significa…
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
Dongxu Li, Junnan Li, Hongdong Li +2
Video-and-language pre-training has shown promising improvements on various downstream tasks. Most previous methods capture cross-modal interactions with a transformer-based multim…
Improving GAN Equilibrium by Raising Spatial Awareness
Jianyuan Wang, Ceyuan Yang, Yinghao Xu +3
The success of Generative Adversarial Networks (GANs) is largely built upon the adversarial training between a generator (G) and a discriminator (D). They are expected to reach a c…
Learning To Segment Dominant Object Motion From Watching Videos
Sahir Shrestha, Mohammad Ali Armin, Hongdong Li +1
Existing deep learning based unsupervised video object segmentation methods still rely on ground-truth segmentation masks to train. Unsupervised in this context only means that no…
HDR-NeRF: High Dynamic Range Neural Radiance Fields
Xin Huang, Qi Zhang, Ying Feng +3
We present High Dynamic Range Neural Radiance Fields (HDR-NeRF) to recover an HDR radiance field from a set of low dynamic range (LDR) views with different exposures. Using the HDR…
Blind Image Decomposition
Junlin Han, Weihao Li, Pengfei Fang +5
We propose and study a novel task named Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that…
Multi-level Motion Attention for Human Motion Prediction
Wei Mao, Miaomiao Liu, Mathieu Salzmann +1
Human motion prediction aims to forecast future human poses given a historical motion. Whether based on recurrent or feed-forward neural networks, existing learning based methods f…
Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance
Ziang Cheng, Hongdong Li, Yuta Asano +2
Recovering the 3D geometry of a purely texture-less object with generally unknown surface reflectance (e.g. non-Lambertian) is regarded as a challenging task in multi-view reconstr…