6 citations · 7 across the 16 of their papers we have counts for
18 papers
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Arbitrary Reading Order Scene Text Spotter with Local Semantics Guidance
Jiahao Lyu, Wei Wang, Dongbao Yang +2
Scene text spotting has attracted the enthusiasm of relative researchers in recent years. Most existing scene text spotters follow the detection-then-recognition paradigm, where th…
First Creating Backgrounds Then Rendering Texts: A New Paradigm for Visual Text Blending
Zhenhang Li, Yan Shu, Weichao Zeng +2
Diffusion models, known for their impressive image generation abilities, have played a pivotal role in the rise of visual text generation. Nevertheless, existing visual text genera…
TextCtrl: Diffusion-based Scene Text Editing with Prior Guidance Control
Weichao Zeng, Yan Shu, Zhenhang Li +2
Centred on content modification and style preservation, Scene Text Editing (STE) remains a challenging task despite considerable progress in text-to-image synthesis and text-driven…
Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval
Gangyan Zeng, Yuan Zhang, Jin Wei +5
Scene text retrieval aims to find all images containing the query text from an image gallery. Current efforts tend to adopt an Optical Character Recognition (OCR) pipeline, which r…