120 citations · 907 across the 57 of their papers we have counts for
59 papers
Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields
Jingbo Zhang, Xiaoyu Li, Ziyu Wan +2
Text-driven 3D scene generation is widely applicable to video gaming, film industry, and metaverse applications that have a large demand for 3D scenes. However, existing text-to-3D…
Learning Neural Duplex Radiance Fields for Real-Time View Synthesis
Ziyu Wan, Christian Richardt, Aljaž Božič +8
Neural radiance fields (NeRFs) enable novel view synthesis with unprecedented visual quality. However, to render photorealistic images, NeRFs require hundreds of deep multilayer pe…
3D Video Loops from Asynchronous Input
Li Ma, Xiaoyu Li, Jing Liao +1
Looping videos are short video clips that can be looped endlessly without visible seams or artifacts. They provide a very attractive way to capture the dynamism of natural scenes.…
AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control
Ruixiang Jiang, Can Wang, Jingbo Zhang +4
Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating…
NeRF-Art: Text-Driven Neural Radiance Fields Stylization
Can Wang, Ruixiang Jiang, Menglei Chai +3
As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains chall…
Robust Point Cloud Segmentation with Noisy Annotations
Shuquan Ye, Dongdong Chen, Songfang Han +1
Point cloud segmentation is a fundamental task in 3D. Despite recent progress on point cloud segmentation with the power of deep networks, current learning methods based on the cle…
Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles
Shuquan Ye, Yujia Xie, Dongdong Chen +4
This paper focuses on analyzing and improving the commonsense ability of recent popular vision-language (VL) models. Despite the great success, we observe that existing VL-models s…
UniColor: A Unified Framework for Multi-Modal Colorization with Transformer
Zhitong Huang, Nanxuan Zhao, Jing Liao
We propose the first unified framework UniColor to support colorization in multiple modalities, including both unconditional and conditional ones, such as stroke, exemplar, text, a…
Adaptive Joint Optimization for 3D Reconstruction with Differentiable Rendering
Jingbo Zhang, Ziyu Wan, Jing Liao
Due to inevitable noises introduced during scanning and quantization, 3D reconstruction via RGB-D sensors suffers from errors both in geometry and texture, leading to artifacts suc…
FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editing
Jingbo Zhang, Xiaoyu Li, Ziyu Wan +2
We propose a Few-shot Dynamic Neural Radiance Field (FDNeRF), the first NeRF-based method capable of reconstruction and expression editing of 3D faces based on a small number of dy…
Bringing Old Films Back to Life
Ziyu Wan, Bo Zhang, Dongdong Chen +1
We present a learning-based framework, recurrent transformer network (RTN), to restore heavily degraded old films. Instead of performing frame-wise restoration, our method is based…
3D Question Answering
Shuquan Ye, Dongdong Chen, Songfang Han +1
Visual Question Answering (VQA) has witnessed tremendous progress in recent years. However, most efforts only focus on the 2D image question answering tasks. In this paper, we pres…
HairCLIP: Design Your Hair by Text and Reference Image
Tianyi Wei, Dongdong Chen, Wenbo Zhou +5
Hair editing is an interesting and challenging problem in computer vision and graphics. Many existing methods require well-drawn sketches or masks as conditional inputs for editing…
CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields
Can Wang, Menglei Chai, Mingming He +2
We present CLIP-NeRF, a multi-modal 3D object manipulation method for neural radiance fields (NeRF). By leveraging the joint language-image embedding space of the recent Contrastiv…
Deblur-NeRF: Neural Radiance Fields from Blurry Images
Li Ma, Xiaoyu Li, Jing Liao +4
Neural Radiance Field (NeRF) has gained considerable attention recently for 3D scene reconstruction and novel view synthesis due to its remarkable synthesis quality. However, image…
Exploring Structure Consistency for Deep Model Watermarking
Jie Zhang, Dongdong Chen, Jing Liao +5
The intellectual property (IP) of Deep neural networks (DNNs) can be easily ``stolen'' by surrogate model attack. There has been significant progress in solutions to protect the IP…
Learning with Noisy Labels for Robust Point Cloud Segmentation
Shuquan Ye, Dongdong Chen, Songfang Han +1
Point cloud segmentation is a fundamental task in 3D. Despite recent progress on point cloud segmentation with the power of deep networks, current deep learning methods based on th…
Deep Portrait Lighting Enhancement with 3D Guidance
Fangzhou Han, Can Wang, Hao Du +1
Despite recent breakthroughs in deep learning methods for image lighting enhancement, they are inferior when applied to portraits because 3D facial information is ignored in their…
Poison Ink: Robust and Invisible Backdoor Attack
Jie Zhang, Dongdong Chen, Qidong Huang +5
Recent research shows deep neural networks are vulnerable to different types of attacks, such as adversarial attack, data poisoning attack and backdoor attack. Among them, backdoor…
PD-GAN: Probabilistic Diverse GAN for Image Inpainting
Hongyu Liu, Ziyu Wan, Wei Huang +3
We propose PD-GAN, a probabilistic diverse GAN for image inpainting. Given an input image with arbitrary hole regions, PD-GAN produces multiple inpainting results with diverse and…
Exemplar-Based 3D Portrait Stylization
Fangzhou Han, Shuquan Ye, Mingming He +2
Exemplar-based portrait stylization is widely attractive and highly desired. Despite recent successes, it remains challenging, especially when considering both texture and geometri…
Let's See Clearly: Contaminant Artifact Removal for Moving Cameras
Xiaoyu Li, Bo Zhang, Jing Liao +1
Contaminants such as dust, dirt and moisture adhering to the camera lens can greatly affect the quality and clarity of the resulting image or video. In this paper, we propose a vid…
Cross-Domain and Disentangled Face Manipulation with 3D Guidance
Can Wang, Menglei Chai, Mingming He +2
Face image manipulation via three-dimensional guidance has been widely applied in various interactive scenarios due to its semantically-meaningful understanding and user-friendly c…
E2Style: Improve the Efficiency and Effectiveness of StyleGAN Inversion
Tianyi Wei, Dongdong Chen, Wenbo Zhou +5
This paper studies the problem of StyleGAN inversion, which plays an essential role in enabling the pretrained StyleGAN to be used for real image editing tasks. The goal of StyleGA…