HuMo AI

Kling 3.0 is an advanced AI video generation model built to produce cinematic-quality videos from text and image prompts. It delivers smoother motion, sharper visuals, and improved physical realism for more lifelike scenes. The model maintains strong character consistency, ensuring stable appearances and controlled facial expressions throughout a video. Enhanced prompt comprehension allows creators to design complex scenes with dynamic camera angles and fluid transitions. Kling 3.0 supports high-resolution outputs that meet professional content standards. Faster rendering speeds help teams reduce production timelines significantly. The platform enables high-quality video creation without relying on traditional filming or expensive production tools.

HunyuanCustom is a multi-modal customized video generation framework that emphasizes subject consistency while supporting image, audio, video, and text conditions. Built upon HunyuanVideo, it introduces a text-image fusion module based on LLaVA for enhanced multi-modal understanding, along with an image ID enhancement module that leverages temporal concatenation to reinforce identity features across frames. To enable audio- and video-conditioned generation, it further proposes modality-specific condition injection mechanisms, an AudioNet module that achieves hierarchical alignment via spatial cross-attention, and a video-driven injection module that integrates latent-compressed conditional video through a patchify-based feature-alignment network. Extensive experiments on single- and multi-subject scenarios demonstrate that HunyuanCustom significantly outperforms state-of-the-art open and closed source methods in terms of ID consistency, realism, and text-video alignment.