182 citations · 574 across the 46 of their papers we have counts for
41 papers · 1 filter
CoCoIns: Consistent Subject Generation via Contrastive Instantiated Concepts
Lee Hsin-Ying, Kelvin C. K. Chan, Ming-Hsuan Yang
While text-to-image generative models can synthesize diverse and faithful content, subject variation across multiple generations limits their application to long-form content gener…
Exploiting Diffusion Prior for Generalizable Dense Prediction
Hsin-Ying Lee, Hung-Yu Tseng, Ming-Hsuan Yang
Contents generated by recent advanced Text-to-Image (T2I) diffusion models are sometimes too imaginative for existing off-the-shelf dense predictors to estimate due to the immitiga…
Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
Guocheng Qian, Jinjie Mai, Abdullah Hamdi +8
We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D meshes generation from a single unposed image in the wild using both2D and 3D priors. In the…
Text-Guided Synthesis of Eulerian Cinemagraphs
Aniruddha Mahapatra, Aliaksandr Siarohin, Hsin-Ying Lee +2
We introduce Text2Cinemagraph, a fully automated method for creating cinemagraphs from text descriptions - an especially challenging task when prompts feature imaginary elements an…
Text2Tex: Text-driven Texture Synthesis via Diffusion Models
Dave Zhenyu Chen, Yawar Siddiqui, Hsin-Ying Lee +2
We present Text2Tex, a novel method for generating high-quality textures for 3D meshes from the given text prompts. Our method incorporates inpainting into a pre-trained depth-awar…
3D generation on ImageNet
Ivan Skorokhodov, Aliaksandr Siarohin, Yinghao Xu +4
Existing 3D-from-2D generators are typically designed for well-curated single-category datasets, where all the objects have (approximately) the same scale, 3D location, and orienta…
Unsupervised Volumetric Animation
Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov +5
We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB vi…
InfiniCity: Infinite-Scale City Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Willi Menapace +4
Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which constructs and renders an unconstrainedly large and 3D-grounded environment from random noi…
3DAvatarGAN: Bridging Domains for Personalized Editable Avatars
Rameen Abdal, Hsin-Ying Lee, Peihao Zhu +4
Modern 3D-GANs synthesize geometry and texture by training on large-scale datasets with a consistent structure. Training such models on stylized, artistic data, with often unknown,…
DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis
Yinghao Xu, Menglei Chai, Zifan Shi +8
Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of obj…
ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes
Ahmed Abdelreheem, Kyle Olszewski, Hsin-Ying Lee +2
The two popular datasets ScanRefer [16] and ReferIt3D [3] connect natural language to real-world 3D data. In this paper, we curate a large-scale and complementary dataset extending…
SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation
Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov +2
In this work, we present a novel framework built to simplify 3D asset generation for amateur users. To enable interactive generation, our method supports a variety of input modalit…
Make-A-Story: Visual Memory Conditioned Consistent Story Generation
Tanzila Rahman, Hsin-Ying Lee, Jian Ren +3
There has been a recent explosion of impressive generative models that can produce high quality images (or videos) conditioned on text descriptions. However, all such approaches re…
Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling
Hsin-Ying Lee, Hung-Ting Su, Bing-Chen Tsai +3
While recent large-scale video-language pre-training made great progress in video question answering, the design of spatial modeling of video-language models is less fine-grained t…
Coarse-to-Fine Point Cloud Registration with SE(3)-Equivariant Representations
Cheng-Wei Lin, Tung-I Chen, Hsin-Ying Lee +2
Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose di…
CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection
Ching-Yu Tseng, Yi-Rong Chen, Hsin-Ying Lee +3
To achieve accurate 3D object detection at a low cost for autonomous driving, many multi-camera methods have been proposed and solved the occlusion problem of monocular approaches.…
Adaptively-Realistic Image Generation from Stroke and Sketch with Diffusion Model
Shin-I Cheng, Yu-Jie Chen, Wei-Chen Chiu +2
Generating images from hand-drawings is a crucial and fundamental task in content creation. The translation is difficult as there exist infinite possibilities and the different use…
Vector Quantized Image-to-Image Translation
Yu-Jie Chen, Shin-I Cheng, Wei-Chen Chiu +2
Current image-to-image translation methods formulate the task with conditional generation models, leading to learning only the recolorization or regional changes as being constrain…
Cross-Modal 3D Shape Generation and Manipulation
Zezhou Cheng, Menglei Chai, Jian Ren +5
Creating and editing the shape and color of 3D objects require tremendous human effort and expertise. Compared to direct manipulation in 3D interfaces, 2D interactions such as sket…
Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features
Chieh Hubert Lin, Hsin-Ying Lee, Hung-Yu Tseng +2
Recent studies show that paddings in convolutional neural networks encode absolute position information which can negatively affect the model performance for certain tasks. However…
Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning
Ligong Han, Jian Ren, Hsin-Ying Lee +5
Most methods for conditional video synthesis use a single modality as the condition. This comes with major limitations. For example, it is problematic for a model conditioned on an…
D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation
Tsung-Han Wu, Yi-Syuan Liou, Shao-Ji Yuan +4
In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations. Active learning, maximizing model performance with…
StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
Min Jin Chong, Hsin-Ying Lee, David Forsyth
Recently, StyleGAN has enabled various image manipulation and editing tasks thanks to the high-quality generation and the disentangled latent space. However, additional architectur…
ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation
Tsung-Han Wu, Yueh-Cheng Liu, Yu-Kai Huang +4
Despite the success of deep learning on supervised point cloud semantic segmentation, obtaining large-scale point-by-point manual annotations is still a significant challenge. To r…