4 papers
UFO: A Unified Approach to Fine-grained Visual Perception via Open-ended Language Interface
Hao Tang, Chenwei Xie, Haiyang Wang +5
Generalist models have achieved remarkable success in both language and vision-language tasks, showcasing the potential of unified modeling. However, effectively integrating fine-g…
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Haiyang Wang, Yue Fan, Muhammad Ferjad Naeem +5
Transformers have become the predominant architecture in foundation models due to their excellent performance across various domains. However, the substantial cost of scaling these…
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Haiyang Wang, Hao Tang, Li Jiang +5
This paper proposes a simple, yet effective framework, called GiT, simultaneously applicable for various vision tasks only with a vanilla ViT. Motivated by the universality of the…
PRED: Pre-training via Semantic Rendering on LiDAR Point Clouds
Hao Yang, Haiyang Wang, Di Dai +1
Pre-training is crucial in 3D-related fields such as autonomous driving where point cloud annotation is costly and challenging. Many recent studies on point cloud pre-training, how…