2 citations · 3 across the 7 of their papers we have counts for
9 papers
Mind-Brush: Integrating Agentic Cognitive Search and Reasoning into Image Generation
Jun He, Junyan Ye, Zilong Huang +6
While text-to-image generation has achieved unprecedented fidelity, the vast majority of existing models function fundamentally as static text-to-pixel decoders. Consequently, they…
DraCo: Draft as CoT for Text-to-Image Preview and Rare Concept Generation
Dongzhi Jiang, Renrui Zhang, Haodong Li +9
Recent unified multimodal large language models (MLLMs) have shown impressive capabilities, incorporating chain-of-thought (CoT) reasoning for enhanced text-to-image generation. Ho…
BLINK-Twice: You see, but do you observe? A Reasoning Benchmark on Visual Perception
Junyan Ye, Dongzhi Jiang, Jun He +6
Recently, Multimodal Large Language Models (MLLMs) have made rapid progress, particularly in enhancing their reasoning capabilities. However, existing reasoning benchmarks still pr…
UrbanFeel: A Comprehensive Benchmark for Temporal and Perceptual Understanding of City Scenes through Human Perspective
Jun He, Yi Lin, Zilong Huang +5
Urban development impacts over half of the global population, making human-centered understanding of its structural and perceptual changes essential for sustainable development. Wh…
Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation
Junyan Ye, Dongzhi Jiang, Zihao Wang +9
Recently, GPT-4o has garnered significant attention for its strong performance in image generation, yet open-source models still lag behind. Several studies have explored distillin…
GPT-ImgEval: A Comprehensive Benchmark for Diagnosing GPT4o in Image Generation
Zhiyuan Yan, Junyan Ye, Weijia Li +7
The recent breakthroughs in OpenAI's GPT4o model have demonstrated surprisingly good capabilities in image generation and editing, resulting in significant excitement in the commun…
LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models
Junyan Ye, Baichuan Zhou, Zilong Huang +12
With the rapid development of AI-generated content, the future internet may be inundated with synthetic data, making the discrimination of authentic and credible multimodal data in…
CrossViewDiff: A Cross-View Diffusion Model for Satellite-to-Street View Synthesis
Weijia Li, Jun He, Junyan Ye +5
Satellite-to-street view synthesis aims at generating a realistic street-view image from its corresponding satellite-view image. Although stable diffusion models have exhibit remar…
Leveraging BEV Paradigm for Ground-to-Aerial Image Synthesis
Junyan Ye, Jun He, Weijia Li +5
Ground-to-aerial image synthesis focuses on generating realistic aerial images from corresponding ground street view images while maintaining consistent content layout, simulating…