14 papers
EmotionDialogCN: A Spontaneous Multimodal Dataset for Mandarin Emotional Dialogue
Yi Zheng, Yifan Xu, Yan Zhou +8
Face-to-face audiovisual interaction is central to human communication, conveying rich emotional and social cues. However, existing multimodal dialogue datasets remain limited by i…
Motion Beyond Morphology: Bootstrapping Cross-Category Motion Transfer from Abstract Motion Representations
Zhixue Fang, Zhimin Zhang, Bi'an Du +6
Video motion transfer aims to animate a target object using dynamics from a reference video. Existing formulations largely rely on fixed structural correspondence, which becomes il…
TARS: Timestep-Aware Data Scaling for 3D-Free Video Re-Shooting
Jiwen Liu, Shujuan Li, Xiaohan Li +5
Video re-shooting aims to regenerate videos with controllable camera motion and viewpoint. Existing methods rely on explicit 3D priors, which are limited by reconstruction quality…
Vera: Identity-Faithful Human Subject-to-Video Generation
Yulong Xu, Xinyue Liu, Shujuan Li +6
Subject-to-video (S2V) generation has made substantial progress in preserving reference subjects across diverse categories, yet generic subject consistency remains insufficient for…
OmniDirector: General Multi-Shot Camera Cloning without Cross-Paired Data
Jiwen Liu, Shujuan Li, Zhixue Fang +8
Cloning camera motion from reference videos is an important task in video generation, as videos provide intuitive and precise control. Existing methods either directly use parametr…
Kling-MotionControl Technical Report
Kling Team, Jialu Chen, Yikang Ding +21
Character animation aims to generate lifelike videos by transferring motion dynamics from a driving video to a reference image. Recent strides in generative models have paved the w…
KlingAvatar 2.0 Technical Report
Kling Team, Jialu Chen, Yikang Ding +25
Avatar video generation models have achieved remarkable progress in recent years. However, prior work exhibits limited efficiency in generating long-duration high-resolution videos…
UnityVideo: Unified Multi-Modal Multi-Task Learning for Enhancing World-Aware Video Generation
Jiehui Huang, Yuechen Zhang, Xu He +7
Recent video generation models demonstrate impressive synthesis capabilities but remain limited by single-modality conditioning, constraining their holistic world understanding. Th…
MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation
Ming Chen, Liyuan Cui, Wenyuan Zhang +9
Recently, interactive digital human video generation has attracted widespread attention and achieved remarkable progress. However, building such a practical system that can interac…
DiffCap: Diffusion-based Real-time Human Motion Capture using Sparse IMUs and a Monocular Camera
Shaohua Pan, Xinyu Yi, Yan Zhou +4
Combining sparse IMUs and a monocular camera is a new promising setting to perform real-time human motion capture. This paper proposes a diffusion-based solution to learn human mot…
SARGes: Semantically Aligned Reliable Gesture Generation via Intent Chain
Nan Gao, Yihua Bao, Dongdong Weng +5
Co-speech gesture generation enhances human-computer interaction realism through speech-synchronized gesture synthesis. However, generating semantically meaningful gestures remains…
ExGes: Expressive Human Motion Retrieval and Modulation for Audio-Driven Gesture Synthesis
Xukun Zhou, Fengxin Li, Ming Chen +7
Audio-driven human gesture synthesis is a crucial task with broad applications in virtual avatars, human-computer interaction, and creative content generation. Despite notable prog…
MotionGPT-2: A General-Purpose Motion-Language Model for Motion Generation and Understanding
Yuan Wang, Di Huang, Yaqi Zhang +5
Generating lifelike human motions from descriptive texts has experienced remarkable research focus in the recent years, propelled by the emerging requirements of digital humans.Des…
Temporal-Aware Refinement for Video-based Human Pose and Shape Recovery
Ming Chen, Yan Zhou, Weihua Jian +2
Though significant progress in human pose and shape recovery from monocular RGB images has been made in recent years, obtaining 3D human motion with high accuracy and temporal cons…