Zobrazeno 1 - 10
of 21 433
pro vyhledávání: '"camera control"'
Precise camera pose control is crucial for video generation with diffusion models. Existing methods require fine-tuning with additional datasets containing paired videos and camera pose annotations, which are both data-intensive and computationally c
Externí odkaz:
http://arxiv.org/abs/2412.06029
Autor:
Bahmani, Sherwin, Skorokhodov, Ivan, Qian, Guocheng, Siarohin, Aliaksandr, Menapace, Willi, Tagliasacchi, Andrea, Lindell, David B., Tulyakov, Sergey
Numerous works have recently integrated 3D camera control into foundational text-to-video models, but the resulting camera control is often imprecise, and video generation quality suffers. In this work, we analyze camera motion from a first principle
Externí odkaz:
http://arxiv.org/abs/2411.18673
Autor:
Feng, Wanquan, Liu, Jiawei, Tu, Pengqi, Qi, Tianhao, Sun, Mingzhen, Ma, Tianxiang, Zhao, Songtao, Zhou, Siyu, He, Qian
Video generation technologies are developing rapidly and have broad potential applications. Among these technologies, camera control is crucial for generating professional-quality videos that accurately meet user expectations. However, existing camer
Externí odkaz:
http://arxiv.org/abs/2411.06525
Image generation today can produce somewhat realistic images from text prompts. However, if one asks the generator to synthesize a particular camera setting such as creating different fields of view using a 24mm lens versus a 70mm lens, the generator
Externí odkaz:
http://arxiv.org/abs/2412.02168
Autor:
Bahmani, Sherwin, Skorokhodov, Ivan, Siarohin, Aliaksandr, Menapace, Willi, Qian, Guocheng, Vasilkovsky, Michael, Lee, Hsin-Ying, Wang, Chaoyang, Zou, Jiaxu, Tagliasacchi, Andrea, Lindell, David B., Tulyakov, Sergey
Modern text-to-video synthesis models demonstrate coherent, photorealistic generation of complex videos from a text description. However, most existing models lack fine-grained control over camera movement, which is critical for downstream applicatio
Externí odkaz:
http://arxiv.org/abs/2407.12781
Cinematographers adeptly capture the essence of the world, crafting compelling visual narratives through intricate camera movements. Witnessing the strides made by large language models in perceiving and interacting with the 3D world, this study expl
Externí odkaz:
http://arxiv.org/abs/2409.17331
High-quality driving video generation is crucial for providing training data for autonomous driving models. However, current generative models rarely focus on enhancing camera motion control under multi-view tasks, which is essential for driving vide
Externí odkaz:
http://arxiv.org/abs/2409.06189
We propose a training-free and robust solution to offer camera movement control for off-the-shelf video diffusion models. Unlike previous work, our method does not require any supervised finetuning on camera-annotated datasets or self-supervised trai
Externí odkaz:
http://arxiv.org/abs/2406.10126
Autor:
Kuang, Zhengfei, Cai, Shengqu, He, Hao, Xu, Yinghao, Li, Hongsheng, Guibas, Leonidas, Wetzstein, Gordon
Research on video generation has recently made tremendous progress, enabling high-quality videos to be generated from text prompts or images. Adding control to the video generation process is an important goal moving forward and recent approaches tha
Externí odkaz:
http://arxiv.org/abs/2405.17414
Controllability plays a crucial role in video generation since it allows users to create desired content. However, existing models largely overlooked the precise control of camera pose that serves as a cinematic language to express deeper narrative n
Externí odkaz:
http://arxiv.org/abs/2404.02101