Improved Hallo: Identity-aware and High-fidelity Audio-Driven Portrait Image Animation
Abstract
Abstract Speech-driven portrait animation generation models have made significant progress in generating realistic and dynamic portrait animations. The class of end-to-end latent diffusion paradigms represented by Hallo17 achieves impressive results in terms of alignment accuracy between audio inputs and visual outputs, encompassing lip movements, expressions and head poses. However, constrained by the suboptimal interaction design between reference portrait information and the denoising U-Net in such architectures, certain frames in the output video sequences suffer from inconsistencies in identity and background preservation. Moreover, the temporal attention within the temporal module operates by incorporating information across frames within each generation unit to capture overall motion trends, but ignoring shorter frame subsequences within the generation unit, consequently losing fine-grained details between adjacent frames. In order to solve the above problems, we take the Hallo pre-trained model17 as the backbone network, and construct a Multi-Source Self Attention (MSSA) to optimize the interaction between reference portrait identity information and denoising U-Net. In addition, we also propose a plug-and-play, training-free method known as Unit-wise Spectral-Blend Temporal Attention (U-SBTA), which enables simultaneously capture local high-frequency facial details from shorter frame subsequences within each generation unit, thereby improving facial fidelity in…
Read the paper
Related studies
- Learning from First-Generation Qualitative Approaches in the IS Discipline: An Evolutionary View and Some Implications for Authors and Evaluators (PART 1/2)
- Commentary on the clinical and preclinical dosage limits of interstitially administered magnetic fluids for therapeutic hyperthermia based on current practice and efficacy models
- Prosthesis: New Technological Opportunities and Innovative Biomedical Devices
- The history and future of neural modeling for cochlear implants
- Ryanodine receptors: waking up from refractoriness
- Novel Transgenic Rabbit Model Sheds Light on the Puzzling Role of Matrix Metalloproteinase-12 in Atherosclerosis
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.