4 citations · 11 across the 11 of their papers we have counts for
6 papers · 1 filter
RetouchIQ: MLLM Agents for Instruction-Based Image Retouching with Generalist Reward
Qiucheng Wu, Jing Shi, Simon Jenni +4
Recent advances in multimodal large language models (MLLMs) have shown great potential for extending vision-language reasoning to professional tool-based image editing, enabling in…
VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos
Qiucheng Wu, Handong Zhao, Zhixin Shu +3
Although recent video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camera trajectories, they still strug…
Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis
Qiucheng Wu, Yujian Liu, Handong Zhao +4
Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generate…
Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models
Qiucheng Wu, Yujian Liu, Handong Zhao +6
Generative models have been widely studied in computer vision. Recently, diffusion models have drawn substantial attention due to the high quality of their generated images. A key…
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices
Yimeng Zhang, Akshay Karkal Kamath, Qiucheng Wu +6
In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stre…
Grasping the Arrow of Time from the Singularity: Decoding Micromotion in Low-dimensional Latent Spaces from StyleGAN
Qiucheng Wu, Yifan Jiang, Junru Wu +5
The disentanglement of StyleGAN latent space has paved the way for realistic and controllable image editing, but does StyleGAN know anything about temporal motion, as it was only t…