38 citations · 38 across the 9 of their papers we have counts for
10 papers
Avatar V: Scaling Video-Reference Avatar Video Generation
Benjamin Liang, Ce Chen, Desmond Lin +20
Generating avatar videos that are not merely visually similar to a target individual but behaviorally recognizable, faithfully reproducing their talking rhythm, gestural tendencies…
Generate Your Talking Avatar from Video Reference
Zujin Guo, Zhenhui Ye, Yi Ren +4
Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target generation. This restricted,…
TransVLM: A Vision-Language Framework and Benchmark for Detecting Any Shot Transitions
Ce Chen, Yi Ren, Yuanming Li +5
Traditional Shot Boundary Detection (SBD) inherently struggles with complex transitions by formulating the task around isolated cut points, frequently yielding corrupted video shot…
Mobile-VTON: High-Fidelity On-Device Virtual Try-On
Zhenchen Wan, Ce Chen, Runqi Lin +5
Virtual try-on (VTON) has recently achieved impressive visual fidelity, but most existing systems require uploading personal photos to cloud-based GPUs, raising privacy concerns an…
Condition Matters in Full-head 3D GANs
Heyuan Li, Huimin Zhang, Yuda Qiu +10
Conditioning is crucial for stable training of full-head 3D GANs. Without any conditioning signal, the model suffers from severe mode collapse, making it impractical to training. H…
CT4D: Consistent Text-to-4D Generation with Animatable Meshes
Ce Chen, Shaoli Huang, Xuelin Chen +4
Text-to-4D generation has recently been demonstrated viable by integrating a 2D image diffusion model with a video diffusion model. However, existing models tend to produce results…
SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representation
Heyuan Li, Ce Chen, Tianhao Shi +4
While recent advances in 3D-aware Generative Adversarial Networks (GANs) have aided the development of near-frontal view human face synthesis, the challenge of comprehensively synt…
DenseMP: Unsupervised Dense Pre-training for Few-shot Medical Image Segmentation
Zhaoxin Fan, Puquan Pan, Zeren Zhang +4
Few-shot medical image semantic segmentation is of paramount importance in the domain of medical image analysis. However, existing methodologies grapple with the challenge of data…
SCoDA: Domain Adaptive Shape Completion for Real Scans
Yushuang Wu, Zizheng Yan, Ce Chen +6
3D shape completion from point clouds is a challenging task, especially from scans of real-world objects. Considering the paucity of 3D shape ground truths for real scans, existing…
Structure-Preserving Super Resolution with Gradient Guidance
Cheng Ma, Yongming Rao, Yean Cheng +3
Structures matter in single image super resolution (SISR). Recent studies benefiting from generative adversarial network (GAN) have promoted the development of SISR by recovering p…