20 citations · 21 across the 4 of their papers we have counts for
4 papers
NoiseAR: AutoRegressing Initial Noise Prior for Diffusion Models
Zeming Li, Xiangyue Liu, Xiangyu Zhang +2
Diffusion models have emerged as powerful generative frameworks, creating data samples by progressively denoising an initial random state. Traditionally, this initial state is samp…
Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets
Weiyu Li, Xuanyang Zhang, Zheng Sun +15
While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamen…
Step-Video-TI2V Technical Report: A State-of-the-Art Text-Driven Image-to-Video Generation Model
Haoyang Huang, Guoqing Ma, Nan Duan +51
We present Step-Video-TI2V, a state-of-the-art text-driven image-to-video generation model with 30B parameters, capable of generating videos up to 102 frames based on both text and…
Align-DETR: Enhancing End-to-end Object Detection with Aligned Loss
Zhi Cai, Songtao Liu, Guodong Wang +3
DETR has set up a simple end-to-end pipeline for object detection by formulating this task as a set prediction problem, showing promising potential. Despite its notable advancement…