Search Results for author: Yijin Li

Found 12 papers, 3 papers with code

Multi-View Neural 3D Reconstruction of Micro-/Nanostructures with Atomic Force Microscopy

1 code implementation21 Jan 2024 Shuo Chen, Mao Peng, Yijin Li, Bing-Feng Ju, Hujun Bao, Yuan-Liu Chen, Guofeng Zhang

However, conventional AFM scanning struggles to reconstruct complex 3D micro-/nanostructures precisely due to limitations such as incomplete sample topography capturing and tip-sample convolution artifacts.

3D Reconstruction Surface Reconstruction

Graph-based Asynchronous Event Processing for Rapid Object Recognition

no code implementations ICCV 2021 Yijin Li, Han Zhou, Bangbang Yang, Ye Zhang, Zhaopeng Cui, Hujun Bao, Guofeng Zhang

Different from traditional video cameras, event cameras capture asynchronous events stream in which each event encodes pixel location, trigger time, and the polarity of the brightness changes.

graph construction Object Recognition

Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor

no code implementations ICCV 2023 Xinyang Liu, Yijin Li, Yanbin Teng, Hujun Bao, Guofeng Zhang, yinda zhang, Zhaopeng Cui

Specifically, we propose a multi-modal implicit scene representation that supports rendering both the signals from the RGB camera and light-weight ToF sensor which drives the optimization by comparing with the raw sensor inputs.

Pose Tracking

FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow

no code implementations8 Jun 2023 Zhaoyang Huang, Xiaoyu Shi, Chao Zhang, Qiang Wang, Yijin Li, Hongwei Qin, Jifeng Dai, Xiaogang Wang, Hongsheng Li

This paper introduces a novel transformer-based network architecture, FlowFormer, along with the Masked Cost Volume AutoEncoding (MCVA) for pretraining it to tackle the problem of optical flow estimation.

Optical Flow Estimation

Context-PIPs: Persistent Independent Particles Demands Spatial Context Features

no code implementations3 Jun 2023 Weikang Bian, Zhaoyang Huang, Xiaoyu Shi, Yitong Dong, Yijin Li, Hongsheng Li

We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos.

Point Tracking

DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation

1 code implementation1 Jun 2023 Xiaoliang Ju, Zhaoyang Huang, Yijin Li, Guofeng Zhang, Yu Qiao, Hongsheng Li

In addition to the scene generation, the final part of DiffInDScene can be used as a post-processing module to refine the 3D reconstruction results from multi-view stereo.

3D Reconstruction Image Generation +1

PATS: Patch Area Transportation with Subdivision for Local Feature Matching

no code implementations CVPR 2023 Junjie Ni, Yijin Li, Zhaoyang Huang, Hongsheng Li, Hujun Bao, Zhaopeng Cui, Guofeng Zhang

However, estimating scale differences between these patches is non-trivial since the scale differences are determined by both relative camera poses and scene structures, and thus spatially varying over image pairs.

Graph Matching Optical Flow Estimation +2

DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image

no code implementations27 Sep 2022 Yijin Li, Xinyang Liu, Wenqi Dong, Han Zhou, Hujun Bao, Guofeng Zhang, yinda zhang, Zhaopeng Cui

Light-weight time-of-flight (ToF) depth sensors are small, cheap, low-energy and have been massively deployed on mobile devices for the purposes like autofocus, obstacle detection, etc.

3D Reconstruction Depth Completion +2

Neural Rendering in a Room: Amodal 3D Understanding and Free-Viewpoint Rendering for the Closed Scene Composed of Pre-Captured Objects

no code implementations5 May 2022 Bangbang Yang, yinda zhang, Yijin Li, Zhaopeng Cui, Sean Fanello, Hujun Bao, Guofeng Zhang

We, as human beings, can understand and picture a familiar scene from arbitrary viewpoints given a single image, whereas this is still a grand challenge for computers.

Data Augmentation Neural Rendering +1

Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering

no code implementations ICCV 2021 Bangbang Yang, yinda zhang, Yinghao Xu, Yijin Li, Han Zhou, Hujun Bao, Guofeng Zhang, Zhaopeng Cui

In this paper, we present a novel neural scene rendering system, which learns an object-compositional neural radiance field and produces realistic rendering with editing capability for a clustered and real-world scene.

Neural Rendering Novel View Synthesis +1

VS-Net: Voting with Segmentation for Visual Localization

1 code implementation CVPR 2021 Zhaoyang Huang, Han Zhou, Yijin Li, Bangbang Yang, Yan Xu, Xiaowei Zhou, Hujun Bao, Guofeng Zhang, Hongsheng Li

To address this problem, we propose a novel visual localization framework that establishes 2D-to-3D correspondences between the query image and the 3D map with a series of learnable scene-specific landmarks.

Segmentation Semantic Segmentation +1

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