1 citations · 1 across the 8 of their papers we have counts for
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Video Generation with Predictive Latents
Yian Zhao, Feng Wang, Qiushan Guo +4
Video Variational Autoencoder (VAE) enables latent video generative modeling by mapping the visual world into compact spatiotemporal latent spaces, improving training efficiency an…
RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models
Zijun Liao, Yian Zhao, Xin Shan +5
Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the pursuit of high-speed inference v…
UI2V-Bench: An Understanding-based Image-to-video Generation Benchmark
Ailing Zhang, Lina Lei, Dehong Kong +7
Generative diffusion models are developing rapidly and attracting increasing attention due to their wide range of applications. Image-to-Video (I2V) generation has become a major f…
Make Your Actor Talk: Generalizable and High-Fidelity Lip Sync with Motion and Appearance Disentanglement
Runyi Yu, Tianyu He, Ailing Zhang +6
We aim to edit the lip movements in talking video according to the given speech while preserving the personal identity and visual details. The task can be decomposed into two sub-p…
FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation
Pengchong Qiao, Lei Shang, Chang Liu +3
Subject-driven generation has garnered significant interest recently due to its ability to personalize text-to-image generation. Typical works focus on learning the new subject's p…
ParCo: Part-Coordinating Text-to-Motion Synthesis
Qiran Zou, Shangyuan Yuan, Shian Du +5
We study a challenging task: text-to-motion synthesis, aiming to generate motions that align with textual descriptions and exhibit coordinated movements. Currently, the part-based…