24 citations · 189 across the 82 of their papers we have counts for
87 papers
RAO-Nav: Probing Omni-Language Models for Zero-shot Semantic Audio-Visual Navigation
Qilang Ye, Meng Liu, Yu Zhou
We explore whether Omni-Language Models (OLMs) can be directly applied to zero-shot Semantic Audio-Visual Navigation (SAVN). Recent work demonstrates that even state-of-the-art spe…
Towards Omni-dimensional GUI Agent Navigation with Masked Trajectory Prediction
Yan Zhang, Pei Fu, Daiqing Wu +8
Graphical User Interface (GUI) Agents autonomously interact with software to fulfill user requests, where GUI navigation stands out as the most critical and challenging capability.…
From Glance to Scrutiny: Progressive Distortion Reasoning for Fine-Grained Image Quality Assessment
Aoting Zhang, Mingze Gao, Dongbao Yang +5
Multi-modal large language models (MLLMs) have demonstrated significant potential in image quality assessment (IQA) by bridging visual perception with descriptive evaluations. Howe…
Knowing Beyond the Known: Reinforced Knowledge Specification for Multi-Label Class-Incremental Learning
Aoting Zhang, Dongbao Yang, Chang Liu +3
Existing class-incremental learning methods struggle in multi-label scenarios (MLCIL) due to the inherent contradiction of learning objectives arising from co-occurring and incompl…
HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better
Gengluo Li, Xingyu Wan, Shangpin Peng +20
We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, information extraction, text-image tr…
Open-Set Visual Text Forensics via Sparse-Constraint Rectified Flow
Jiangling Zhang, Shuxuan Gao, Zeyu Chen +2
Rapidly evolving Generative AI enables sophisticated visual text manipulations that increasingly evade current forensic detectors. Existing discriminative models often overfit spec…
MVEI & EmObserver: Empowering MLLM-Oriented Visual Emotional Intelligence via Emotion Statement Judgement
Daiqing Wu, Dongbao Yang, Jiashu Yao +4
Affective Image Content Analysis (AICA) aims to recognize and understand emotions elicited by visual content, representing an indispensable step toward Artificial General Intellige…
Orthogonal Knowledge Refreshing for Domain-Incremental Object Detection
Aoting Zhang, Dongbao Yang, Chang Liu +3
Domain-incremental object detection (DIOD) requires models to continually adapt to new domains while preserving prior knowledge. Recently, parameter-efficient fine-tuning offers a…
ChartArena: Benchmarking Chart Parsing across Languages, Scenarios, and Formats
Shangpin Peng, Gengluo Li, Xingyu Wan +10
Charts are a primary medium for conveying quantitative and relational information, yet systematically evaluating chart parsing models remains difficult. Existing benchmarks focus o…
StrucTab: A Structured Optimization Framework for Table Parsing
Gengluo Li, Shangpin Peng, Chengquan Zhang +10
Table parsing aims to convert table images into structured, machine-readable representations, a task requiring the joint perception of complex spatial layouts and textual content.…
UniTranslator: A Unified Multi-modal Framework for End-to-end In-Image Machine Translation
Jiahao Lyu, Pei Fu, Zhenhang Li +6
In-Image Machine Translation (IIMT) aims to translate scene text in an image and render the translated text back into the original regions while preserving the overall visual appea…
Focus, Align, and Sustain: Counteracting Gradient Dilution in Incremental Object Detection
Aoting Zhang, Dongbao Yang, Chang Liu +2
Adapting Detection Transformers to Incremental Object Detection (IOD) poses a systemic challenge, as set-based optimization is inherently destabilized by sequential learning. In th…
Multimodal Emotion Recognition with Large Language Models
Hongrui Zhang, Daiqing Wu, Yangyang Li +4
Multimodal Emotion Recognition (MER) focuses on identifying and interpreting emotions from modality-compound inputs. Closely mirroring human cognitive processes in real-world envir…
Beyond Detection: A Structure-Aware Framework for Scene Text Tracking
Chenmin Yu, Liu Yu, Daiqing Wu +3
Modern visual object trackers show impressive results on general targets, yet their performance drops substantially when dealing with scene text. Although currently underexplored,…
DRS-GUI: Dynamic Region Search for Training-Free GUI Grounding
Yichao Liu, Huawen Shen, Liu Yu +3
GUI agents powered by Multimodal Large Language Models (MLLMs) have demonstrated impressive capability in understanding and executing user instructions. However, accurately groundi…
Masked Next-Scale Prediction for Self-supervised Scene Text Recognition
Zhuohao Chen, Zeng Li, Yifei Zhang +2
Scene Text Recognition requires modeling visual structures that evolve from coarse layouts to fine-grained character strokes. Training such models relies on large amounts of annota…
StyleTextGen: Style-Conditioned Multilingual Scene Text Generation
Zeyu Chen, Fangmin Zhao, Yan Shu +3
Style-conditioned scene text generation faces unique challenges in extracting precise text styles from complex backgrounds and maintaining fine-grained style consistency across cha…
Chronicles-OCR: A Cross-Temporal Perception Benchmark for the Evolutionary Trajectory of Chinese Characters
Gengluo Li, Shangpin Peng, Xingyu Wan +16
Vision Large Language Models (VLLMs) have achieved remarkable success in modern text-rich visual understanding. However, their perceptual robustness in the face of the continuous m…
Learn where to Click from Yourself: On-Policy Self-Distillation for GUI Grounding
Yan Zhang, Daiqing Wu, Huawen Shen +2
Graphical User Interface (GUI) grounding maps natural language instructions to the visual coordinates of target elements and serves as a core capability for autonomous GUI agents.…
Towards Real-World Document Parsing via Realistic Scene Synthesis and Document-Aware Training
Gengluo Li, Pengyuan Lyu, Chengquan Zhang +7
Document parsing has recently advanced with multimodal large language models (MLLMs) that directly map document images to structured outputs. Traditional cascaded pipelines depend…
IMTBench: A Multi-Scenario Cross-Modal Collaborative Evaluation Benchmark for In-Image Machine Translation
Jiahao Lyu, Pei Fu, Zhenhang Li +7
End-to-end In-Image Machine Translation (IIMT) aims to convert text embedded within an image into a target language while preserving the original visual context, layout, and render…
MMTIT-Bench: A Multilingual and Multi-Scenario Benchmark with Cognition-Perception-Reasoning Guided Text-Image Machine Translation
Gengluo Li, Chengquan Zhang, Yupu Liang +9
End-to-end text-image machine translation (TIMT), which directly translates textual content in images across languages, is crucial for real-world multilingual scene understanding.…
Semantic Audio-Visual Navigation in Continuous Environments
Yichen Zeng, Hebaixu Wang, Meng Liu +4
Audio-visual navigation enables embodied agents to navigate toward sound-emitting targets by leveraging both auditory and visual cues. However, most existing approaches rely on pre…
Echo: Towards Advanced Audio Comprehension via Audio-Interleaved Reasoning
Daiqing Wu, Xuan Zhang, Dongbao Yang +7
The maturation of Large Audio Language Models (LALMs) has raised growing expectations for them to comprehend complex audio much like humans. Current efforts primarily replicate tex…