17 citations · 37 across the 20 of their papers we have counts for
21 papers
D-Prism: Differentiable Primitives for Structured Dynamic Modeling
Xingyuan Yu, Yijin Li, Chong Zeng +3
Capturing both geometry and rigid motion for structured dynamic objects, like multi-part assemblies or jointed mechanisms, remains a key challenge. Existing dynamic methods, such a…
Neural Field-Based 3D Surface Reconstruction of Microstructures from Multi-Detector Signals in Scanning Electron Microscopy
Shuo Chen, Yijin Li, Xi Zheng +1
The 3D characterization of microstructures is crucial for understanding and designing functional materials. However, the scanning electron microscope (SEM), widely used in scientif…
CoProSketch: Controllable and Progressive Sketch Generation with Diffusion Model
Ruohao Zhan, Yijin Li, Yisheng He +6
Sketches serve as fundamental blueprints in artistic creation because sketch editing is easier and more intuitive than pixel-level RGB image editing for painting artists, yet sketc…
OpticFusion: Multi-Modal Neural Implicit 3D Reconstruction of Microstructures by Fusing White Light Interferometry and Optical Microscopy
Shuo Chen, Yijin Li, Guofeng Zhang
White Light Interferometry (WLI) is a precise optical tool for measuring the 3D topography of microstructures. However, conventional WLI cannot capture the natural color of a sampl…
GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking
Weikang Bian, Zhaoyang Huang, Xiaoyu Shi +3
4D video control is essential in video generation as it enables the use of sophisticated lens techniques, such as multi-camera shooting and dolly zoom, which are currently unsuppor…
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding
Yitong Dong, Yijin Li, Zhaoyang Huang +6
In this paper, we propose a novel multi-view stereo (MVS) framework that gets rid of the depth range prior. Unlike recent prior-free MVS methods that work in a pair-wise manner, ou…
ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
Junjie Ni, Guofeng Zhang, Guanglin Li +4
We tackle the efficiency problem of learning local feature matching. Recent advancements have given rise to purely CNN-based and transformer-based approaches, each augmented with d…
BlinkVision: A Benchmark for Optical Flow, Scene Flow and Point Tracking Estimation using RGB Frames and Events
Yijin Li, Yichen Shen, Zhaoyang Huang +9
Recent advances in event-based vision suggest that these systems complement traditional cameras by providing continuous observation without frame rate limitations and a high dynami…
BlinkTrack: Feature Tracking over 80 FPS via Events and Images
Yichen Shen, Yijin Li, Shuo Chen +5
Event cameras, known for their high temporal resolution and ability to capture asynchronous changes, have gained significant attention for their potential in feature tracking, espe…
Multi-View Neural 3D Reconstruction of Micro-/Nanostructures with Atomic Force Microscopy
Shuo Chen, Mao Peng, Yijin Li +4
Atomic Force Microscopy (AFM) is a widely employed tool for micro-/nanoscale topographic imaging. However, conventional AFM scanning struggles to reconstruct complex 3D micro-/nano…
Graph-based Asynchronous Event Processing for Rapid Object Recognition
Yijin Li, Han Zhou, Bangbang Yang +4
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 brightn…
Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor
Xinyang Liu, Yijin Li, Yanbin Teng +4
Light-weight time-of-flight (ToF) depth sensors are compact and cost-efficient, and thus widely used on mobile devices for tasks such as autofocus and obstacle detection. However,…
FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow
Zhaoyang Huang, Xiaoyu Shi, Chao Zhang +6
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…
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features
Weikang Bian, Zhaoyang Huang, Xiaoyu Shi +3
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 trajec…
DiffInDScene: Diffusion-based High-Quality 3D Indoor Scene Generation
Xiaoliang Ju, Zhaoyang Huang, Yijin Li +3
We present DiffInDScene, a novel framework for tackling the problem of high-quality 3D indoor scene generation, which is challenging due to the complexity and diversity of the indo…
BlinkFlow: A Dataset to Push the Limits of Event-based Optical Flow Estimation
Yijin Li, Zhaoyang Huang, Shuo Chen +5
Event cameras provide high temporal precision, low data rates, and high dynamic range visual perception, which are well-suited for optical flow estimation. While data-driven optica…
PATS: Patch Area Transportation with Subdivision for Local Feature Matching
Junjie Ni, Yijin Li, Zhaoyang Huang +4
Local feature matching aims at establishing sparse correspondences between a pair of images. Recently, detector-free methods present generally better performance but are not satisf…
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image
Yijin Li, Xinyang Liu, Wenqi Dong +5
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,…
Neural Rendering in a Room: Amodal 3D Understanding and Free-Viewpoint Rendering for the Closed Scene Composed of Pre-Captured Objects
Bangbang Yang, Yinda Zhang, Yijin Li +4
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. We hereby pr…
Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering
Bangbang Yang, Yinda Zhang, Yinghao Xu +5
Implicit neural rendering techniques have shown promising results for novel view synthesis. However, existing methods usually encode the entire scene as a whole, which is generally…
VS-Net: Voting with Segmentation for Visual Localization
Zhaoyang Huang, Han Zhou, Yijin Li +6
Visual localization is of great importance in robotics and computer vision. Recently, scene coordinate regression based methods have shown good performance in visual localization i…