INR Smooth: Interframe noise relation-based smooth video synthesis on diffusion models. [PDF]
PLoS OneYu C, Han C, Zhang C.
europepmc +2 more sources
Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator [PDF]
Neural Information Processing Systems, 2023 Text-to-video is a rapidly growing research area that aims to generate a semantic, identical, and temporal coherence sequence of frames that accurately align with the input text prompt. This study focuses on zero-shot text-to-video generation considering
Hanzhuo Huang +5 more
semanticscholar +1 more source
Algoritma End of File dan Rijndael pada Steganografi Video
JRST: Jurnal Riset Sains dan Teknologi, 2021 Teknik penyembunyian pesan dalam media digital dikenal dengan istilah steganografi. Peneltitian diranccang untuk membuat steganografi video, pesan yang disisipkan berupa teks terlebih dahulu dienkripsi dengan algoritma Rijndael.
Imam Riadi, Sunardi Sunardi, Dwi Aryanto
doaj +1 more source
Noise-Resistant Video Channel Identification
Security and Communication Networks, 2022 As the video streaming traffic grows exponentially nowadays, variable bitrate (VBR) encoding has been widely utilized by modern live video streaming service providers, such as YouTube, TikTok, and Twitch. However, video bitrate can be a delicate fingerprint of the video streaming, leading to risks of privacy leakage.
Mingkai Wang +3 more
openaire +1 more source
VMC: Video Motion Customization Using Temporal Attention Adaption for Text-to-Video Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2023 Text-to-video diffusion models have advanced video generation significantly. However, customizing these models to generate videos with tailored motions presents a substantial challenge.
Hyeonho Jeong +2 more
semanticscholar +1 more source
Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution [PDF]
Computer Vision and Pattern Recognition, 2023 Text-based diffusion models have exhibited remarkable success in generation and editing, showing great promise for enhancing visual content with their generative prior.
Shangchen Zhou +4 more
semanticscholar +1 more source
MomentDiff: Generative Video Moment Retrieval from Random to Real [PDF]
Neural Information Processing Systems, 2023 Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language description.
P. Li +7 more
semanticscholar +1 more source
DiffusionRet: Generative Text-Video Retrieval with Diffusion Model [PDF]
IEEE International Conference on Computer Vision, 2023 Existing text-video retrieval solutions are, in essence, discriminant models focused on maximizing the conditional likelihood, i.e., p(candidates|query).
Peng Jin +7 more
semanticscholar +1 more source
Partial Differential Equations-Based Iterative Denoising Algorithm for Movie Images
Advances in Mathematical Physics, 2021 Film video noise can usually be defined as the error information visible on the video image, caused by the digital signal system. This distortion is inevitably present in the video obtained by various camera equipment.
Pingli Sun +3 more
doaj +1 more source
Edit-A-Video: Single Video Editing with Object-Aware Consistency [PDF]
Asian Conference on Machine Learning, 2023 Despite the fact that text-to-video (TTV) model has recently achieved remarkable success, there have been few approaches on TTV for its extension to video editing.
Chaehun Shin +4 more
semanticscholar +1 more source