5 papers
DiT-Reward: Generative Representations for Text-to-Image Reward Modeling
Yuanming Yang, Guoqing Ma, Bo Wang +5
Can representations learned for image generation also support the evaluation of generated images? We study text-to-image reward prediction as a downstream task of generative repres…
AdaCodec: A Predictive Visual Code for Video MLLMs
Haowen Hou, Zhen Huang, Zheming Liang +8
Video is temporally redundant: adjacent frames usually share most objects, background, and layout. Yet existing video multimodal large language models (video MLLMs) usually encode…
EasyVideoR1: Easier RL for Video Understanding
Chuanyu Qin, Chenxu Yang, Qingyi Si +6
Reinforcement learning from verifiable rewards (RLVR) has demonstrated remarkable effectiveness in improving the reasoning capabilities of large language models. As models evolve i…
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…
Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model
Guoqing Ma, Haoyang Huang, Kun Yan +112
We present Step-Video-T2V, a state-of-the-art text-to-video pre-trained model with 30B parameters and the ability to generate videos up to 204 frames in length. A deep compression…