19 citations · 46 across the 60 of their papers we have counts for
8 papers · 1 filter
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Unified Multimodal models (UMMs) built on a single architecture have shown impressive performance in both understanding and generation. We identify a fundamental challenge that lie…
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration
Jiaqi Shi, Yuechan Li, Xulong Zhang +2
High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Existing acceleration strategi…
MIRRORTALK: Forging Personalized Avatars Via Disentangled Style and Hierarchical Motion Control
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Synthesizing personalized talking faces that uphold and highlight a speaker's unique style while maintaining lip-sync accuracy remains a significant challenge. A primary limitation…
ESARM: 3D Emotional Speech-to-Animation via Reward Model from Automatically-Ranked Demonstrations
Xulong Zhang, Xiaoyang Qu, Haoxiang Shi +2
This paper proposes a novel 3D speech-to-animation (STA) generation framework designed to address the shortcomings of existing models in producing diverse and emotionally resonant…
EmoTalker: Emotionally Editable Talking Face Generation via Diffusion Model
Bingyuan Zhang, Xulong Zhang, Ning Cheng +3
In recent years, the field of talking faces generation has attracted considerable attention, with certain methods adept at generating virtual faces that convincingly imitate human…
CP-EB: Talking Face Generation with Controllable Pose and Eye Blinking Embedding
Jianzong Wang, Yimin Deng, Ziqi Liang +3
This paper proposes a talking face generation method named "CP-EB" that takes an audio signal as input and a person image as reference, to synthesize a photo-realistic people talki…
AOSR-Net: All-in-One Sandstorm Removal Network
Yazhong Si, Xulong Zhang, Fan Yang +3
Most existing sandstorm image enhancement methods are based on traditional theory and prior knowledge, which often restrict their applicability in real-world scenarios. In addition…
DiffTalker: Co-driven audio-image diffusion for talking faces via intermediate landmarks
Zipeng Qi, Xulong Zhang, Ning Cheng +2
Generating realistic talking faces is a complex and widely discussed task with numerous applications. In this paper, we present DiffTalker, a novel model designed to generate lifel…