collaborators

6 papers

cs.CV2026

DrawAI: Agentic Benchmark and Workflow for Making Raster Images Editable

Pu Cao, Qingye Kong, Xuedan Yin +5

Recent image-generation models and multimodal agents can produce high-quality visuals for increasingly complex visual communication tasks. Yet their raster outputs remain difficult…

cs.CV2026

Fourier Series Coder: A Novel Perspective on Angle Boundary Discontinuity Problem for Oriented Object Detection

Minghong Wei, Pu Cao, Zhihao Chen +3

With the rapid advancement of intelligent driving and remote sensing, oriented object detection has gained widespread attention. However, achieving high-precision performance is fu…

cs.CV2026

A Tilted Seesaw: Revisiting Autoencoder Trade-off for Controllable Diffusion

Pu Cao, Yiyang Ma, Feng Zhou +3

In latent diffusion models, the autoencoder (AE) is typically expected to balance two capabilities: faithful reconstruction and a generation-friendly latent space (e.g., low gFID).…

cs.CV2026

Controllable Generation with Text-to-Image Diffusion Models: A Survey

Pu Cao, Feng Zhou, Qing Song +1

In the rapidly advancing realm of visual generation, diffusion models have revolutionized the landscape, marking a significant shift in capabilities with their impressive text-guid…

cs.CV2025

Preliminary Explorations with GPT-4o(mni) Native Image Generation

Pu Cao, Feng Zhou, Junyi Ji +8

Recently, the visual generation ability by GPT-4o(mni) has been unlocked by OpenAI. It demonstrates a very remarkable generation capability with excellent multimodal condition unde…

cs.CV2025

Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generation

Pu Cao, Feng Zhou, Lu Yang +2

In-domain generation aims to perform a variety of tasks within a specific domain, such as unconditional generation, text-to-image, image editing, 3D generation, and more. Early res…