activity
20202026
most citedLogiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning

22 citations · 31 across the 21 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

ChartAct: A Benchmark for Dynamic Chart Understanding

Muye Huang, Lin Wu, Lingling Zhang +5

Charts are widely used to present complex data for analysis and decision making. Existing chart understanding benchmarks mainly focus on static charts, but real-world charts are of…

cs.CV2026

ReDiffuse: Rotation Equivariant Diffusion Model for Multi-focus Image Fusion

Bo Li, Tingting Bao, Lingling Zhang +3

Diffusion models have achieved impressive performance on multi-focus image fusion (MFIF). However, a key challenge in applying diffusion models to the ill-posed MFIF problem is tha…

cs.CV2026

SketchVL: Policy Optimization via Fine-Grained Credit Assignment for Chart Understanding and More

Muye Huang, Lingling Zhang, Yifei Li +2

Charts are high-density visual carriers of complex data and medium for information extraction and analysis. Due to the need for precise and complex visual reasoning, automated char…

cs.CV2025

CoFFT: Chain of Foresight-Focus Thought for Visual Language Models

Xinyu Zhang, Yuxuan Dong, Lingling Zhang +5

Despite significant advances in Vision Language Models (VLMs), they remain constrained by the complexity and redundancy of visual input. When images contain large amounts of irrele…

cs.CV2025

Neurodynamics-Driven Coupled Neural P Systems for Multi-Focus Image Fusion

Bo Li, Yunkuo Lei, Tingting Bao +5

Multi-focus image fusion (MFIF) is a crucial technique in image processing, with a key challenge being the generation of decision maps with precise boundaries. However, traditional…

cs.CV2025

ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding

Muye Huang, Lingling Zhang, Jie Ma +6

Charts are high-density visualization carriers for complex data, serving as a crucial medium for information extraction and analysis. Automated chart understanding poses significan…

cs.CV2024

Diagram-Driven Course Questions Generation

Xinyu Zhang, Lingling Zhang, Yanrui Wu +6

Visual Question Generation (VQG) research focuses predominantly on natural images while neglecting the diagram, which is a critical component in educational materials. To meet the…

cs.CV2024

Few-shot Open Relation Extraction with Gaussian Prototype and Adaptive Margin

Tianlin Guo, Lingling Zhang, Jiaxin Wang +4

Few-shot relation extraction with none-of-the-above (FsRE with NOTA) aims at predicting labels in few-shot scenarios with unknown classes. FsRE with NOTA is more challenging than t…

cs.CV2024

GoT-CQA: Graph-of-Thought Guided Compositional Reasoning for Chart Question Answering

Lingling Zhang, Muye Huang, QianYing Wang +3

Chart Question Answering (CQA) aims at answering questions based on the visual chart content, which plays an important role in chart sumarization, business data analysis, and data…

cs.CV2024

VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution Reasoning

Muye Huang, Lingling Zhang, Lai Han +3

Charts are widely used for data visualization across various fields, including education, research, and business. Chart Question Answering (CQA) is an emerging task focused on the…

cs.CV2024

EvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding

Muye Huang, Han Lai, Xinyu Zhang +4

Chart understanding enables automated data analysis for humans, which requires models to achieve highly accurate visual comprehension. While existing Visual Language Models (VLMs)…

cs.CV2022★ 1 cited

GPTR: Gestalt-Perception Transformer for Diagram Object Detection

Xin Hu, Lingling Zhang, Jun Liu +3

Diagram object detection is the key basis of practical applications such as textbook question answering. Because the diagram mainly consists of simple lines and color blocks, its v…

cs.CV2021

RL-CSDia: Representation Learning of Computer Science Diagrams

Shaowei Wang, LingLing Zhang, Xuan Luo +3

Recent studies on computer vision mainly focus on natural images that express real-world scenes. They achieve outstanding performance on diverse tasks such as visual question answe…

cs.CV2020

ZSTAD: Zero-Shot Temporal Activity Detection

Lingling Zhang, Xiaojun Chang, Jun Liu +4

An integral part of video analysis and surveillance is temporal activity detection, which means to simultaneously recognize and localize activities in long untrimmed videos. Curren…