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Tianfu Wu

4 papers hereh-index 359 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Tianfu Wu — 47 papers, h 32
  • Tianfu Wu — 4 papers, h 3
  • Tianfu Wu — 3 papers, h 0
  • Tianfu Wu — 3 papers, h 2
  • Tianfu Wu — 2 papers, h 4
  • Tianfu Wu — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222025
most citedHolistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning

51 citations · 51 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

ScaleLSD: Scalable Deep Line Segment Detection Streamlined

Zeran Ke, Bin Tan, Xianwei Zheng +3

This paper studies the problem of Line Segment Detection (LSD) for the characterization of line geometry in images, with the aim of learning a domain-agnostic robust LSD model that…

cs.CV2024

A Pixel Is Worth More Than One 3D Gaussians in Single-View 3D Reconstruction

Jianghao Shen, Nan Xue, Tianfu Wu

Learning 3D scene representation from a single-view image is a long-standing fundamental problem in computer vision, with the inherent ambiguity in predicting contents unseen from…

cs.CV2024

Multi-View Attentive Contextualization for Multi-View 3D Object Detection

Xianpeng Liu, Ce Zheng, Ming Qian +5

We present Multi-View Attentive Contextualization (MvACon), a simple yet effective method for improving 2D-to-3D feature lifting in query-based multi-view 3D (MV3D) object detectio…

cs.CV2022★ 51 cited

Holistically-Attracted Wireframe Parsing: From Supervised to Self-Supervised Learning

Nan Xue, Tianfu Wu, Song Bai +4

This article presents Holistically-Attracted Wireframe Parsing (HAWP), a method for geometric analysis of 2D images containing wireframes formed by line segments and junctions. HAW…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.