3 citations · 6 across the 24 of their papers we have counts for
6 papers · 1 filter
NAS-LoRA: Empowering Parameter-Efficient Fine-Tuning for Visual Foundation Models with Searchable Adaptation
Renqi Chen, Haoyang Su, Shixiang Tang
The Segment Anything Model (SAM) has emerged as a powerful visual foundation model for image segmentation. However, adapting SAM to specific downstream tasks, such as medical and a…
Interleaving Reasoning for Better Text-to-Image Generation
Wenxuan Huang, Shuang Chen, Zheyong Xie +15
Unified multimodal understanding and generation models recently have achieve significant improvement in image generation capability, yet a large gap remains in instruction followin…
Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining
Weizhen He, Yunfeng Yan, Shixiang Tang +4
Human-centric perception is the core of diverse computer vision tasks and has been a long-standing research focus. However, previous research studied these human-centric tasks indi…
CMT: A Cascade MAR with Topology Predictor for Multimodal Conditional CAD Generation
Jianyu Wu, Yizhou Wang, Xiangyu Yue +5
While accurate and user-friendly Computer-Aided Design (CAD) is crucial for industrial design and manufacturing, existing methods still struggle to achieve this due to their over-s…
Human-Centric Foundation Models: Perception, Generation and Agentic Modeling
Shixiang Tang, Yizhou Wang, Lu Chen +4
Human understanding and generation are critical for modeling digital humans and humanoid embodiments. Recently, Human-centric Foundation Models (HcFMs) inspired by the success of g…
EgoAgent: A Joint Predictive Agent Model in Egocentric Worlds
Lu Chen, Yizhou Wang, Shixiang Tang +6
Learning an agent model that behaves like humans-capable of jointly perceiving the environment, predicting the future, and taking actions from a first-person perspective-is a funda…