24 citations · 189 across the 82 of their papers we have counts for
24 papers · 1 filter
EmoCaliber: Advancing Reliable Visual Emotion Comprehension via Confidence Verbalization and Calibration
Daiqing Wu, Dongbao Yang, Can Ma +1
Visual Emotion Comprehension (VEC) aims to infer sentiment polarities or emotion categories from affective cues embedded in images. In recent years, Multimodal Large Language Model…
HunyuanOCR Technical Report
Hunyuan Vision Team, Pengyuan Lyu, Xingyu Wan +29
This paper presents HunyuanOCR, a commercial-grade, open-source, and lightweight (1B parameters) Vision-Language Model (VLM) dedicated to OCR tasks. The architecture comprises a Na…
Robust Multimodal Sentiment Analysis of Image-Text Pairs by Distribution-Based Feature Recovery and Fusion
Daiqing Wu, Dongbao Yang, Yu Zhou +1
As posts on social media increase rapidly, analyzing the sentiments embedded in image-text pairs has become a popular research topic in recent years. Although existing works achiev…
ComMark: Covert and Robust Black-Box Model Watermarking with Compressed Samples
Yunfei Yang, Xiaojun Chen, Zhendong Zhao +3
The rapid advancement of deep learning has turned models into highly valuable assets due to their reliance on massive data and costly training processes. However, these models are…
Bridging Visual Affective Gap: Borrowing Textual Knowledge by Learning from Noisy Image-Text Pairs
Daiqing Wu, Dongbao Yang, Yu Zhou +1
Visual emotion recognition (VER) is a longstanding field that has garnered increasing attention with the advancement of deep neural networks. Although recent studies have achieved…
SUGAR: Learning Skeleton Representation with Visual-Motion Knowledge for Action Recognition
Qilang Ye, Yu Zhou, Lian He +10
Large Language Models (LLMs) hold rich implicit knowledge and powerful transferability. In this paper, we explore the combination of LLMs with the human skeleton to perform action…
When Eyes and Ears Disagree: Can MLLMs Discern Audio-Visual Confusion?
Qilang Ye, Wei Zeng, Meng Liu +4
Can Multimodal Large Language Models (MLLMs) discern confused objects that are visually present but audio-absent? To study this, we introduce a new benchmark, AV-ConfuseBench, whic…
Task-Aware 3D Affordance Segmentation via 2D Guidance and Geometric Refinement
Lian He, Meng Liu, Qilang Ye +3
Understanding 3D scene-level affordances from natural language instructions is essential for enabling embodied agents to interact meaningfully in complex environments. However, thi…
Customizing Visual Emotion Evaluation for MLLMs: An Open-vocabulary, Multifaceted, and Scalable Approach
Daiqing Wu, Dongbao Yang, Sicheng Zhao +2
Recently, Multimodal Large Language Models (MLLMs) have achieved exceptional performance across diverse tasks, continually surpassing previous expectations regarding their capabili…
TADoc: Robust Time-Aware Document Image Dewarping
Fangmin Zhao, Weichao Zeng, Zhenhang Li +2
Flattening curved, wrinkled, and rotated document images captured by portable photographing devices, termed document image dewarping, has become an increasingly important task with…
Gather and Trace: Rethinking Video TextVQA from an Instance-oriented Perspective
Yan Zhang, Gangyan Zeng, Daiqing Wu +5
Video text-based visual question answering (Video TextVQA) aims to answer questions by explicitly reading and reasoning about the text involved in a video. Most works in this field…
Uni-DocDiff: A Unified Document Restoration Model Based on Diffusion
Fangmin Zhao, Weichao Zeng, Zhenhang Li +4
Removing various degradations from damaged documents greatly benefits digitization, downstream document analysis, and readability. Previous methods often treat each restoration tas…
Class-Agnostic Region-of-Interest Matching in Document Images
Demin Zhang, Jiahao Lyu, Zhijie Shen +1
Document understanding and analysis have received a lot of attention due to their widespread application. However, existing document analysis solutions, such as document layout ana…
Beyond Cropped Regions: New Benchmark and Corresponding Baseline for Chinese Scene Text Retrieval in Diverse Layouts
Gengluo Li, Huawen Shen, Yu Zhou
Chinese scene text retrieval is a practical task that aims to search for images containing visual instances of a Chinese query text. This task is extremely challenging because Chin…
When Semantics Mislead Vision: Mitigating Large Multimodal Models Hallucinations in Scene Text Spotting and Understanding
Yan Shu, Hangui Lin, Yexin Liu +7
Large Multimodal Models (LMMs) have achieved impressive progress in visual perception and reasoning. However, when confronted with visually ambiguous or non-semantic scene text, th…
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
Daiqing Wu, Dongbao Yang, Sicheng Zhao +2
The advancements in Multimodal Large Language Models (MLLMs) have enabled various multimodal tasks to be addressed under a zero-shot paradigm. This paradigm sidesteps the cost of m…
The Devil is in Fine-tuning and Long-tailed Problems:A New Benchmark for Scene Text Detection
Tianjiao Cao, Jiahao Lyu, Weichao Zeng +2
Scene text detection has seen the emergence of high-performing methods that excel on academic benchmarks. However, these detectors often fail to replicate such success in real-worl…
VidText: Towards Comprehensive Evaluation for Video Text Understanding
Zhoufaran Yang, Yan Shu, Jing Wang +8
Visual texts embedded in videos carry rich semantic information, which is crucial for both holistic video understanding and fine-grained reasoning about local human actions. Howeve…
The Role of Video Generation in Enhancing Data-Limited Action Understanding
Wei Li, Dezhao Luo, Dongbao Yang +3
Video action understanding tasks in real-world scenarios always suffer data limitations. In this paper, we address the data-limited action understanding problem by bridging data sc…
Visual Text Processing: A Comprehensive Review and Unified Evaluation
Yan Shu, Weichao Zeng, Fangmin Zhao +9
Visual text is a crucial component in both document and scene images, conveying rich semantic information and attracting significant attention in the computer vision community. Bey…
Linguistics-aware Masked Image Modeling for Self-supervised Scene Text Recognition
Yifei Zhang, Chang Liu, Jin Wei +4
Text images are unique in their dual nature, encompassing both visual and linguistic information. The visual component encompasses structural and appearance-based features, while t…
Specifying What You Know or Not for Multi-Label Class-Incremental Learning
Aoting Zhang, Dongbao Yang, Chang Liu +2
Existing class incremental learning is mainly designed for single-label classification task, which is ill-equipped for multi-label scenarios due to the inherent contradiction of le…
DCA: Dividing and Conquering Amnesia in Incremental Object Detection
Aoting Zhang, Dongbao Yang, Chang Liu +3
Incremental object detection (IOD) aims to cultivate an object detector that can continuously localize and recognize novel classes while preserving its performance on previous clas…
Beyond Flat Text: Dual Self-inherited Guidance for Visual Text Generation
Minxing Luo, Zixun Xia, Liaojun Chen +7
In real-world images, slanted or curved texts, especially those on cans, banners, or badges, appear as frequently, if not more so, than flat texts due to artistic design or layout…