activity
20212024
most citedPET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Fine-Grained Scene Image Classification with Modality-Agnostic Adapter

Yiqun Wang, Zhao Zhou, Xiangcheng Du +3

When dealing with the task of fine-grained scene image classification, most previous works lay much emphasis on global visual features when doing multi-modal feature fusion. In oth…

cs.CV20241 cited

NocPlace: Nocturnal Visual Place Recognition via Generative and Inherited Knowledge Transfer

Bingxi Liu, Yiqun Wang, Huaqi Tao +5

Visual Place Recognition (VPR) is crucial in computer vision, aiming to retrieve database images similar to a query image from an extensive collection of known images. However, lik…

cs.CV20232 cited

PET-NeuS: Positional Encoding Tri-Planes for Neural Surfaces

Yiqun Wang, Ivan Skorokhodov, Peter Wonka

A signed distance function (SDF) parametrized by an MLP is a common ingredient of neural surface reconstruction. We build on the successful recent method NeuS to extend it by three…

cs.LG20231 cited

Learning Harmonic Molecular Representations on Riemannian Manifold

Yiqun Wang, Yuning Shen, Shi Chen +3

Molecular representation learning plays a crucial role in AI-assisted drug discovery research. Encoding 3D molecular structures through Euclidean neural networks has become the pre…

cs.CV2023

BlobGAN-3D: A Spatially-Disentangled 3D-Aware Generative Model for Indoor Scenes

Qian Wang, Yiqun Wang, Michael Birsak +1

3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images…

cs.CV2022

DS-MVSNet: Unsupervised Multi-view Stereo via Depth Synthesis

Jingliang Li, Zhengda Lu, Yiqun Wang +2

In recent years, supervised or unsupervised learning-based MVS methods achieved excellent performance compared with traditional methods. However, these methods only use the probabi…