Search Results for author:
Found 18 papers, 8 papers with code
DetailGen3D: Generative 3D Geometry Enhancement via Data-Dependent Flow
Modern 3D generation methods can rapidly create shapes from sparse or single views, but their outputs often lack geometric detail due to computational constraints.
DreamCraft3D++: Efficient Hierarchical 3D Generation with Multi-Plane Reconstruction Model
We introduce DreamCraft3D++, an extension of DreamCraft3D that enables efficient high-quality generation of complex 3D assets.
Human4DiT: 360-degree Human Video Generation with 4D Diffusion Transformer
We present a novel approach for generating 360-degree high-quality, spatio-temporally coherent human videos from a single image.
DeepSeek-VL: Towards Real-World Vision-Language Understanding
The DeepSeek-VL family (both 1. 3B and 7B models) showcases superior user experiences as a vision-language chatbot in real-world applications, achieving state-of-the-art or competitive performance across a wide range of visual-language benchmarks at the same model size while maintaining robust performance on language-centric benchmarks.
Ranked #100 on
Visual Question Answering
on MM-Vet
DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
The rapid development of open-source large language models (LLMs) has been truly remarkable.
RAM-Avatar: Real-time Photo-Realistic Avatar from Monocular Videos with Full-body Control
This paper focuses on advancing the applicability of human avatar learning methods by proposing RAM-Avatar which learns a Real-time photo-realistic Avatar that supports full-body control from Monocular videos.
VectorTalker: SVG Talking Face Generation with Progressive Vectorisation
To address these, we propose a novel scalable vector graphic reconstruction and animation method, dubbed VectorTalker.
InvertAvatar: Incremental GAN Inversion for Generalized Head Avatars
While high fidelity and efficiency are central to the creation of digital head avatars, recent methods relying on 2D or 3D generative models often experience limitations such as shape distortion, expression inaccuracy, and identity flickering.
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
The score distillation from this 3D-aware diffusion prior provides view-consistent guidance for the scene.
HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field
The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved.
Control4D: Efficient 4D Portrait Editing with Text
We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions.
StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video
Results and experiments demonstrate the superiority of our method in terms of image quality, full portrait video generation, and real-time re-animation compared to existing facial reenactment methods.
High-fidelity Facial Avatar Reconstruction from Monocular Video with Generative Priors
Compared with existing works, we obtain superior novel view synthesis results and faithfully face reenactment performance.
Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
We propose a novel 3D GAN framework for unsupervised learning of generative, high-quality and 3D-consistent facial avatars from unstructured 2D images.
DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras
At its core is a novel diffusion-based stereo module, which introduces diffusion models, a type of powerful generative models, into the iterative stereo matching network.
IDE-3D: Interactive Disentangled Editing for High-Resolution 3D-aware Portrait Synthesis
Existing 3D-aware facial generation methods face a dilemma in quality versus editability: they either generate editable results in low resolution or high-quality ones with no editing flexibility.
FENeRF: Face Editing in Neural Radiance Fields
2D GANs can generate high fidelity portraits but with low view consistency.
BusTime: Which is the Right Prediction Model for My Bus Arrival Time?
With the rise of big data technologies, many smart transportation applications have been rapidly developed in recent years including bus arrival time predictions.
