Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

🎥 Introducing Hailuo's Subject Reference: Revolutionizing Character Consistency in Video Creation 🔥 We’re excited to present Hailuo's S2V-01 model, a groundbreaking innovation in AI video generation that tackles one of the industry’s biggest challenges: maintaining consistent, realistic facial features and identity across dynamic video content, regardless of camera angles...

692,382 görüntüleme • 1 yıl önce •via X (Twitter)

11 Yorum

Hailuo AI (MiniMax) profil fotoğrafı
Hailuo AI (MiniMax)1 yıl önce

reference images

Freepik profil fotoğrafı
Freepik1 yıl önce

🚀 Introducing Freepik AI video generator. Everything you need to create high-quality, physically accurate videos in one place. 🤩

Apple Dog profil fotoğrafı
Apple Dog1 yıl önce

The possibilities are endless… amazing🍎🫶

Crack GPT profil fotoğrafı
Crack GPT1 yıl önce

Also accept me into your artist program 😭🫡

Anna 🌍☮️ profil fotoğrafı
Anna 🌍☮️1 yıl önce

Bullish on Hailuo and $apple

Nim Eshed 𝕏🦋 profil fotoğrafı
Nim Eshed 𝕏🦋1 yıl önce

Love it

heart profil fotoğrafı
heart1 yıl önce

Just keeps getting better! 🍎

Nim Eshed 𝕏🦋 profil fotoğrafı
Nim Eshed 𝕏🦋1 yıl önce

Love it so much

David Lemanowicz profil fotoğrafı
David Lemanowicz1 yıl önce

I think we crashed the site...

ForeverCurtis.Xrp.Bruh🔺ᚱᚹᛟ profil fotoğrafı
ForeverCurtis.Xrp.Bruh🔺ᚱᚹᛟ1 yıl önce

the only limit is your own imagination! 🍎🐶

Brent Lynch profil fotoğrafı
Brent Lynch1 yıl önce

It's ON! ;)

Benzer Videolar

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model with Gradio demo local demo: This paper studies the human image animation task, which aims to generate a video of a certain reference identity following a particular motion sequence. Existing animation works typically employ the frame-warping technique to animate the reference image towards the target motion. Despite achieving reasonable results, these approaches face challenges in maintaining temporal consistency throughout the animation due to the lack of temporal modeling and poor preservation of reference identity. In this work, we introduce MagicAnimate, a diffusion-based framework that aims at enhancing temporal consistency, preserving reference image faithfully, and improving animation fidelity. To achieve this, we first develop a video diffusion model to encode temporal information. Second, to maintain the appearance coherence across frames, we introduce a novel appearance encoder to retain the intricate details of the reference image. Leveraging these two innovations, we further employ a simple video fusion technique to encourage smooth transitions for long video animation. Empirical results demonstrate the superiority of our method over baseline approaches on two benchmarks. Notably, our approach outperforms the strongest baseline by over 38% in terms of video fidelity on the challenging TikTok dancing dataset. Code and model will be made available.

AK

810,024 görüntüleme • 2 yıl önce