3 citations · 5 across the 6 of their papers we have counts for
6 papers · 1 filter
PointAlign: Feature-Level Alignment Regularization for 3D Vision-Language Models
Yuanhao Su, Shaofeng Zhang, Xiaosong Jia +1
The development of 3D Vision-Language Models (VLMs), crucial for applications in robotics, autonomous driving, and augmented reality, is severely constrained by the scarcity of pai…
Inference-Time Scaling for Diffusion Models beyond Scaling Denoising Steps
Nanye Ma, Shangyuan Tong, Haolin Jia +8
Generative models have made significant impacts across various domains, largely due to their ability to scale during training by increasing data, computational resources, and model…
KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities
Hsin-Ping Huang, Xinyi Wang, Yonatan Bitton +8
Recent advances in text-to-image generation have improved the quality of synthesized images, but evaluations mainly focus on aesthetics or alignment with text prompts. Thus, it rem…
A Versatile Diffusion Transformer with Mixture of Noise Levels for Audiovisual Generation
Gwanghyun Kim, Alonso Martinez, Yu-Chuan Su +8
Training diffusion models for audiovisual sequences allows for a range of generation tasks by learning conditional distributions of various input-output combinations of the two mod…
Instruct-Imagen: Image Generation with Multi-modal Instruction
Hexiang Hu, Kelvin C. K. Chan, Yu-Chuan Su +9
This paper presents instruct-imagen, a model that tackles heterogeneous image generation tasks and generalizes across unseen tasks. We introduce *multi-modal instruction* for image…
Fine-grained Controllable Video Generation via Object Appearance and Context
Hsin-Ping Huang, Yu-Chuan Su, Deqing Sun +4
Text-to-video generation has shown promising results. However, by taking only natural languages as input, users often face difficulties in providing detailed information to precise…