activity
20162025
most citedTC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content

6 citations · 24 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2025

Foundation Model Insights and a Multi-Model Approach for Superior Fine-Grained One-shot Subset Selection

Zhijing Wan, Zhixiang Wang, Zheng Wang +2

One-shot subset selection serves as an effective tool to reduce deep learning training costs by identifying an informative data subset based on the information extracted by an info…

cs.CV2025

ReSeDis: A Dataset for Referring-based Object Search across Large-Scale Image Collections

Ziling Huang, Yidan Zhang, Shin'ichi Satoh

Large-scale visual search engines are expected to solve a dual problem at once: (i) locate every image that truly contains the object described by a sentence and (ii) identify the…

cs.CV2025

Towards Ball Spin and Trajectory Analysis in Table Tennis Broadcast Videos via Physically Grounded Synthetic-to-Real Transfer

Daniel Kienzle, Robin Schön, Rainer Lienhart +1

Analyzing a player's technique in table tennis requires knowledge of the ball's 3D trajectory and spin. While, the spin is not directly observable in standard broadcasting videos,…

cs.CV20244 cited

Matting by Generation

Zhixiang Wang, Baiang Li, Jian Wang +4

This paper introduces an innovative approach for image matting that redefines the traditional regression-based task as a generative modeling challenge. Our method harnesses the cap…

cs.CV20246 cited

TC-OCR: TableCraft OCR for Efficient Detection & Recognition of Table Structure & Content

Avinash Anand, Raj Jaiswal, Pijush Bhuyan +5

The automatic recognition of tabular data in document images presents a significant challenge due to the diverse range of table styles and complex structures. Tables offer valuable…

cs.CV20243 cited

RanLayNet: A Dataset for Document Layout Detection used for Domain Adaptation and Generalization

Avinash Anand, Raj Jaiswal, Mohit Gupta +7

Large ground-truth datasets and recent advances in deep learning techniques have been useful for layout detection. However, because of the restricted layout diversity of these data…