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Omni-Video 2: Scaling MLLM-Conditioned Diffusion for Unified Video Generation and Editing
Hao Yang, Zhiyu Tan, Jia Gong +7
We present Omni-Video 2, a scalable and computationally efficient model that connects pretrained multimodal large-language models (MLLMs) with video diffusion models for unified vi…
Diff-Aid: Inference-time Adaptive Interaction Denoising for Rectified Text-to-Image Generation
Binglei Li, Mengping Yang, Zhiyu Tan +2
Recent text-to-image (T2I) diffusion models have achieved remarkable advancement, yet faithfully following complex textual descriptions remains challenging due to insufficient inte…
Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Vision
Luozheng Qin, Jia Gong, Yuqing Sun +6
Chain-of-Thought (CoT) reasoning has been widely adopted to enhance Large Language Models (LLMs) by decomposing complex tasks into simpler, sequential subtasks. However, extending…
Omni-Video: Democratizing Unified Video Understanding and Generation
Zhiyu Tan, Hao Yang, Luozheng Qin +3
Notable breakthroughs in unified understanding and generation modeling have led to remarkable advancements in image understanding, reasoning, production and editing, yet current fo…
Cockatiel: Ensembling Synthetic and Human Preferenced Training for Detailed Video Caption
Luozheng Qin, Zhiyu Tan, Mengping Yang +2
Video Detailed Captioning (VDC) is a crucial task for vision-language bridging, enabling fine-grained descriptions of complex video content. In this paper, we first comprehensively…
E2ED^2:Direct Mapping from Noise to Data for Enhanced Diffusion Models
Zhiyu Tan, WenXu Qian, Hesen Chen +3
Diffusion models have established themselves as the de facto primary paradigm in visual generative modeling, revolutionizing the field through remarkable success across various div…