2 citations · 4 across the 13 of their papers we have counts for
7 papers · 1 filter
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation
Yongxin Wang, Meng Cao, Haokun Lin +5
Multimodal large language models (MLLMs) have achieved remarkable progress on various visual question answering and reasoning tasks leveraging instruction fine-tuning specific data…
Learning Interaction-aware 3D Gaussian Splatting for One-shot Hand Avatars
Xuan Huang, Hanhui Li, Wanquan Liu +4
In this paper, we propose to create animatable avatars for interacting hands with 3D Gaussian Splatting (GS) and single-image inputs. Existing GS-based methods designed for single…
GarmentAligner: Text-to-Garment Generation via Retrieval-augmented Multi-level Corrections
Shiyue Zhang, Zheng Chong, Xujie Zhang +4
General text-to-image models bring revolutionary innovation to the fields of arts, design, and media. However, when applied to garment generation, even the state-of-the-art text-to…
AutoStudio: Crafting Consistent Subjects in Multi-turn Interactive Image Generation
Junhao Cheng, Xi Lu, Hanhui Li +5
As cutting-edge Text-to-Image (T2I) generation models already excel at producing remarkable single images, an even more challenging task, i.e., multi-turn interactive image generat…
Rethink Predicting the Optical Flow with the Kinetics Perspective
Yuhao Cheng, Siru Zhang, Yiqiang Yan
Optical flow estimation is one of the fundamental tasks in low-level computer vision, which describes the pixel-wise displacement and can be used in many other tasks. From the appa…
TheaterGen: Character Management with LLM for Consistent Multi-turn Image Generation
Junhao Cheng, Baiqiao Yin, Kaixin Cai +9
Recent advances in diffusion models can generate high-quality and stunning images from text. However, multi-turn image generation, which is of high demand in real-world scenarios,…
ConsistentID: Portrait Generation with Multimodal Fine-Grained Identity Preserving
Jiehui Huang, Xiao Dong, Wenhui Song +9
Diffusion-based technologies have made significant strides, particularly in personalized and customized facialgeneration. However, existing methods face challenges in achieving hig…