10 citations · 28 across the 17 of their papers we have counts for
16 papers · 1 filter
Attribute-Grounded Selective Reasoning for Artwork Emotion Understanding with Multimodal Large Language Models
Cheng Zhang, Yuer Liu, Zhiyu Zhou +2
Multimodal large language models (MLLMs) can produce fluent artwork emotion explanations, but they often suffer from attribute flooding: they enumerate many visible formal attribut…
CookAnything: A Framework for Flexible and Consistent Multi-Step Recipe Image Generation
Ruoxuan Zhang, Bin Wen, Hongxia Xie +5
Cooking is a sequential and visually grounded activity, where each step such as chopping, mixing, or frying carries both procedural logic and visual semantics. While recent diffusi…
TriDF: Evaluating Perception, Detection, and Hallucination for Interpretable DeepFake Detection
Jian-Yu Jiang-Lin, Kang-Yang Huang, Ling Zou +11
Advances in generative modeling have made it increasingly easy to fabricate realistic portrayals of individuals, creating serious risks for security, communication, and public trus…
RecipeGen: A Step-Aligned Multimodal Benchmark for Real-World Recipe Generation
Ruoxuan Zhang, Jidong Gao, Bin Wen +4
Creating recipe images is a key challenge in food computing, with applications in culinary education and multimodal recipe assistants. However, existing datasets lack fine-grained…
EmoArt: A Multidimensional Dataset for Emotion-Aware Artistic Generation
Cheng Zhang, Hongxia xie, Bin Wen +3
With the rapid advancement of diffusion models, text-to-image generation has achieved significant progress in image resolution, detail fidelity, and semantic alignment, particularl…
Single Document Image Highlight Removal via A Large-Scale Real-World Dataset and A Location-Aware Network
Lu Pan, Yu-Hsuan Huang, Hongxia Xie +4
Reflective documents often suffer from specular highlights under ambient lighting, severely hindering text readability and degrading overall visual quality. Although recent deep le…
Foreground Focus: Enhancing Coherence and Fidelity in Camouflaged Image Generation
Pei-Chi Chen, Yi Yao, Chan-Feng Hsu +4
Camouflaged image generation is emerging as a solution to data scarcity in camouflaged vision perception, offering a cost-effective alternative to data collection and labeling. Rec…
RecipeGen: A Benchmark for Real-World Recipe Image Generation
Ruoxuan Zhang, Hongxia Xie, Yi Yao +6
Recipe image generation is an important challenge in food computing, with applications from culinary education to interactive recipe platforms. However, there is currently no real-…
Perspective-Aware Teaching: Adapting Knowledge for Heterogeneous Distillation
Jhe-Hao Lin, Yi Yao, Chan-Feng Hsu +3
Knowledge distillation (KD) involves transferring knowledge from a pre-trained heavy teacher model to a lighter student model, thereby reducing the inference cost while maintaining…
The Fabrication of Reality and Fantasy: Scene Generation with LLM-Assisted Prompt Interpretation
Yi Yao, Chan-Feng Hsu, Jhe-Hao Lin +5
In spite of recent advancements in text-to-image generation, limitations persist in handling complex and imaginative prompts due to the restricted diversity and complexity of train…
EmoVIT: Revolutionizing Emotion Insights with Visual Instruction Tuning
Hongxia Xie, Chu-Jun Peng, Yu-Wen Tseng +4
Visual Instruction Tuning represents a novel learning paradigm involving the fine-tuning of pre-trained language models using task-specific instructions. This paradigm shows promis…
Lightweight Deep Learning for Resource-Constrained Environments: A Survey
Hou-I Liu, Marco Galindo, Hongxia Xie +4
Over the past decade, the dominance of deep learning has prevailed across various domains of artificial intelligence, including natural language processing, computer vision, and bi…
Most Important Person-guided Dual-branch Cross-Patch Attention for Group Affect Recognition
Hongxia Xie, Ming-Xian Lee, Tzu-Jui Chen +4
Group affect refers to the subjective emotion that is evoked by an external stimulus in a group, which is an important factor that shapes group behavior and outcomes. Recognizing g…
Technical Report for Valence-Arousal Estimation in ABAW2 Challenge
Hong-Xia Xie, I-Hsuan Li, Ling Lo +2
In this work, we describe our method for tackling the valence-arousal estimation challenge from ABAW2 ICCV-2021 Competition. The competition organizers provide an in-the-wild Aff-W…
An Overview of Facial Micro-Expression Analysis: Data, Methodology and Challenge
Hong-Xia Xie, Ling Lo, Hong-Han Shuai +1
Facial micro-expressions indicate brief and subtle facial movements that appear during emotional communication. In comparison to macro-expressions, micro-expressions are more chall…
MER-GCN: Micro Expression Recognition Based on Relation Modeling with Graph Convolutional Network
Ling Lo, Hong-Xia Xie, Hong-Han Shuai +1
Micro-Expression (ME) is the spontaneous, involuntary movement of a face that can reveal the true feeling. Recently, increasing researches have paid attention to this field combing…