Search Results for author: Haibin Huang

Found 51 papers, 27 papers with code

InterFusion: Text-Driven Generation of 3D Human-Object Interaction

no code implementations22 Mar 2024 Sisi Dai, Wenhao Li, Haowen Sun, Haibin Huang, Chongyang Ma, Hui Huang, Kai Xu, Ruizhen Hu

In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner.

Human-Object Interaction Detection Object +1

VRMM: A Volumetric Relightable Morphable Head Model

no code implementations6 Feb 2024 Haotian Yang, Mingwu Zheng, Chongyang Ma, Yu-Kun Lai, Pengfei Wan, Haibin Huang

In this paper, we introduce the Volumetric Relightable Morphable Model (VRMM), a novel volumetric and parametric facial prior for 3D face modeling.

3D Face Reconstruction Self-Supervised Learning

Direct-a-Video: Customized Video Generation with User-Directed Camera Movement and Object Motion

no code implementations5 Feb 2024 Shiyuan Yang, Liang Hou, Haibin Huang, Chongyang Ma, Pengfei Wan, Di Zhang, Xiaodong Chen, Jing Liao

In practice, users often desire the ability to control object motion and camera movement independently for customized video creation.

Object Video Generation

TopCoW: Benchmarking Topology-Aware Anatomical Segmentation of the Circle of Willis (CoW) for CTA and MRA

1 code implementation29 Dec 2023 Kaiyuan Yang, Fabio Musio, Yihui Ma, Norman Juchler, Johannes C. Paetzold, Rami Al-Maskari, Luciano Höher, Hongwei Bran Li, Ibrahim Ethem Hamamci, Anjany Sekuboyina, Suprosanna Shit, Houjing Huang, Diana Waldmannstetter, Florian Kofler, Fernando Navarro, Martin Menten, Ivan Ezhov, Daniel Rueckert, Iris Vos, Ynte Ruigrok, Birgitta Velthuis, Hugo Kuijf, Julien Hämmerli, Catherine Wurster, Philippe Bijlenga, Laura Westphal, Jeroen Bisschop, Elisa Colombo, Hakim Baazaoui, Andrew Makmur, James Hallinan, Bene Wiestler, Jan S. Kirschke, Roland Wiest, Emmanuel Montagnon, Laurent Letourneau-Guillon, Adrian Galdran, Francesco Galati, Daniele Falcetta, Maria A. Zuluaga, Chaolong Lin, Haoran Zhao, Zehan Zhang, Sinyoung Ra, Jongyun Hwang, HyunJin Park, Junqiang Chen, Marek Wodzinski, Henning Müller, Pengcheng Shi, Wei Liu, Ting Ma, Cansu Yalçin, Rachika E. Hamadache, Joaquim Salvi, Xavier Llado, Uma Maria Lal-Trehan Estrada, Valeriia Abramova, Luca Giancardo, Arnau Oliver, Jialu Liu, Haibin Huang, Yue Cui, Zehang Lin, Yusheng Liu, Shunzhi Zhu, Tatsat R. Patel, Vincent M. Tutino, Maysam Orouskhani, Huayu Wang, Mahmud Mossa-Basha, Chengcheng Zhu, Maximilian R. Rokuss, Yannick Kirchhoff, Nico Disch, Julius Holzschuh, Fabian Isensee, Klaus Maier-Hein, Yuki Sato, Sven Hirsch, Susanne Wegener, Bjoern Menze

The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology.

Anatomy Benchmarking +1

I2V-Adapter: A General Image-to-Video Adapter for Diffusion Models

no code implementations27 Dec 2023 Xun Guo, Mingwu Zheng, Liang Hou, Yuan Gao, Yufan Deng, Pengfei Wan, Di Zhang, Yufan Liu, Weiming Hu, ZhengJun Zha, Haibin Huang, Chongyang Ma

I2V-Adapter adeptly propagates the unnoised input image to subsequent noised frames through a cross-frame attention mechanism, maintaining the identity of the input image without any changes to the pretrained T2V model.

Video Generation

MotionCrafter: One-Shot Motion Customization of Diffusion Models

1 code implementation8 Dec 2023 Yuxin Zhang, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, WeiMing Dong, Changsheng Xu

The essence of a video lies in its dynamic motions, including character actions, object movements, and camera movements.

Disentanglement Motion Disentanglement +3

Agents meet OKR: An Object and Key Results Driven Agent System with Hierarchical Self-Collaboration and Self-Evaluation

no code implementations28 Nov 2023 Yi Zheng, Chongyang Ma, Kanle Shi, Haibin Huang

In this study, we introduce the concept of OKR-Agent designed to enhance the capabilities of Large Language Models (LLMs) in task-solving.

Towards Practical Capture of High-Fidelity Relightable Avatars

no code implementations8 Sep 2023 Haotian Yang, Mingwu Zheng, Wanquan Feng, Haibin Huang, Yu-Kun Lai, Pengfei Wan, Zhongyuan Wang, Chongyang Ma

Specifically, TRAvatar is trained with dynamic image sequences captured in a Light Stage under varying lighting conditions, enabling realistic relighting and real-time animation for avatars in diverse scenes.

3D Keypoint Estimation Using Implicit Representation Learning

no code implementations20 Jun 2023 Xiangyu Zhu, Dong Du, Haibin Huang, Chongyang Ma, Xiaoguang Han

Inspired by the recent success of advanced implicit representation in reconstruction tasks, we explore the idea of using an implicit field to represent keypoints.

Keypoint Estimation Representation Learning

Multi-Modal Face Stylization with a Generative Prior

no code implementations29 May 2023 Mengtian Li, Yi Dong, Minxuan Lin, Haibin Huang, Pengfei Wan, Chongyang Ma

We also introduce a two-stage training strategy, where we train the encoder in the first stage to align the feature maps with StyleGAN and enable a faithful reconstruction of input faces.

Face Generation

ProSpect: Prompt Spectrum for Attribute-Aware Personalization of Diffusion Models

3 code implementations25 May 2023 Yuxin Zhang, WeiMing Dong, Fan Tang, Nisha Huang, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Oliver Deussen, Changsheng Xu

We apply ProSpect in various personalized attribute-aware image generation applications, such as image-guided or text-driven manipulations of materials, style, and layout, achieving previously unattainable results from a single image input without fine-tuning the diffusion models.

Attribute Disentanglement +1

Semi-Weakly Supervised Object Kinematic Motion Prediction

no code implementations CVPR 2023 Gengxin Liu, Qian Sun, Haibin Huang, Chongyang Ma, Yulan Guo, Li Yi, Hui Huang, Ruizhen Hu

First, although 3D dataset with fully annotated motion labels is limited, there are existing datasets and methods for object part semantic segmentation at large scale.

motion prediction Object +3

A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive Learning

1 code implementation9 Mar 2023 Yuxin Zhang, Fan Tang, WeiMing Dong, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Changsheng Xu

Our framework consists of three key components, i. e., a parallel contrastive learning scheme for style representation and style transfer, a domain enhancement module for effective learning of style distribution, and a generative network for style transfer.

Contrastive Learning Representation Learning +1

HairStep: Transfer Synthetic to Real Using Strand and Depth Maps for Single-View 3D Hair Modeling

1 code implementation CVPR 2023 Yujian Zheng, Zirong Jin, Moran Li, Haibin Huang, Chongyang Ma, Shuguang Cui, Xiaoguang Han

We firmly think an intermediate representation is essential, but we argue that orientation map using the dominant filtering-based methods is sensitive to uncertain noise and far from a competent representation.

Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance

1 code implementation28 Feb 2023 Xueyi Liu, Ji Zhang, Ruizhen Hu, Haibin Huang, He Wang, Li Yi

Category-level articulated object pose estimation aims to estimate a hierarchy of articulation-aware object poses of an unseen articulated object from a known category.

Disentanglement Object +1

LitAR: Visually Coherent Lighting for Mobile Augmented Reality

1 code implementation15 Jan 2023 Yiqin Zhao, Chongyang Ma, Haibin Huang, Tian Guo

In this work, we present the design and implementation of a lighting reconstruction framework called LitAR that enables realistic and visually-coherent rendering.

Explicit Motion Disentangling for Efficient Optical Flow Estimation

1 code implementation ICCV 2023 Changxing Deng, Ao Luo, Haibin Huang, Shaodan Ma, Jiangyu Liu, Shuaicheng Liu

In this paper, we propose a novel framework for optical flow estimation that achieves a good balance between performance and efficiency.

Motion Estimation Optical Flow Estimation

Inversion-Based Style Transfer with Diffusion Models

1 code implementation CVPR 2023 Yuxin Zhang, Nisha Huang, Fan Tang, Haibin Huang, Chongyang Ma, WeiMing Dong, Changsheng Xu

Our key idea is to learn artistic style directly from a single painting and then guide the synthesis without providing complex textual descriptions.

Denoising Style Transfer +1

DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylization

1 code implementation19 Nov 2022 Nisha Huang, Yuxin Zhang, Fan Tang, Chongyang Ma, Haibin Huang, Yong Zhang, WeiMing Dong, Changsheng Xu

Despite the impressive results of arbitrary image-guided style transfer methods, text-driven image stylization has recently been proposed for transferring a natural image into a stylized one according to textual descriptions of the target style provided by the user.

Denoising Image Stylization

Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learning

1 code implementation19 May 2022 Yuxin Zhang, Fan Tang, WeiMing Dong, Haibin Huang, Chongyang Ma, Tong-Yee Lee, Changsheng Xu

Our framework consists of three key components, i. e., a multi-layer style projector for style code encoding, a domain enhancement module for effective learning of style distribution, and a generative network for image style transfer.

Contrastive Learning Image Stylization +1

Towards Self-Supervised Category-Level Object Pose and Size Estimation

no code implementations6 Mar 2022 Yisheng He, Haoqiang Fan, Haibin Huang, Qifeng Chen, Jian Sun

Instead, we propose a label-free method that learns to enforce the geometric consistency between category template mesh and observed object point cloud under a self-supervision manner.

Point cloud completion via structured feature maps using a feedback network

no code implementations17 Feb 2022 Zejia Su, Haibin Huang, Chongyang Ma, Hui Huang, Ruizhen Hu

To efficiently exploit local structures and enhance point distribution uniformity, we propose IFNet, a point upsampling module with a self-correction mechanism that can progressively refine details of the generated dense point cloud.

Point Cloud Completion

Implicit Neural Deformation for Sparse-View Face Reconstruction

no code implementations5 Dec 2021 Moran Li, Haibin Huang, Yi Zheng, Mengtian Li, Nong Sang, Chongyang Ma

In this work, we present a new method for 3D face reconstruction from sparse-view RGB images.

3D Face Reconstruction

iShape: A First Step Towards Irregular Shape Instance Segmentation

no code implementations30 Sep 2021 Lei Yang, Yan Zi Wei, Yisheng He, Wei Sun, Zhenhang Huang, Haibin Huang, Haoqiang Fan

In this paper, we introduce a brand new dataset to promote the study of instance segmentation for objects with irregular shapes.

Instance Segmentation Segmentation +1

Scene Synthesis via Uncertainty-Driven Attribute Synchronization

1 code implementation ICCV 2021 Haitao Yang, Zaiwei Zhang, Siming Yan, Haibin Huang, Chongyang Ma, Yi Zheng, Chandrajit Bajaj, QiXing Huang

This task is challenging because 3D scenes exhibit diverse patterns, ranging from continuous ones, such as object sizes and the relative poses between pairs of shapes, to discrete patterns, such as occurrence and co-occurrence of objects with symmetrical relationships.

Attribute

Task-Aware Sampling Layer for Point-Wise Analysis

no code implementations9 Jul 2021 Yiqun Lin, Lichang Chen, Haibin Huang, Chongyang Ma, Xiaoguang Han, Shuguang Cui

Sampling, grouping, and aggregation are three important components in the multi-scale analysis of point clouds.

Keypoint Detection Point Cloud Completion +1

HPNet: Deep Primitive Segmentation Using Hybrid Representations

1 code implementation ICCV 2021 Siming Yan, Zhenpei Yang, Chongyang Ma, Haibin Huang, Etienne Vouga, QiXing Huang

This paper introduces HPNet, a novel deep-learning approach for segmenting a 3D shape represented as a point cloud into primitive patches.

Clustering Segmentation

D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

1 code implementation26 Mar 2021 Youwei Li, Haibin Huang, Lanpeng Jia, Haoqiang Fan, Shuaicheng Liu

Rethinking both, we learn the distribution of underlying high-frequency details in a discrete form and propose a two-stage pipeline: divergence stage to convergence stage.

Image Super-Resolution SSIM

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

3 code implementations CVPR 2021 Yisheng He, Haibin Huang, Haoqiang Fan, Qifeng Chen, Jian Sun

Moreover, at the output representation stage, we designed a simple but effective 3D keypoints selection algorithm considering the texture and geometry information of objects, which simplifies keypoint localization for precise pose estimation.

6D Pose Estimation Representation Learning

NBNet: Noise Basis Learning for Image Denoising with Subspace Projection

3 code implementations CVPR 2021 Shen Cheng, Yuzhi Wang, Haibin Huang, Donghao Liu, Haoqiang Fan, Shuaicheng Liu

Subsequently, image denosing can be achieved by selecting corresponding basis of the signal subspace and projecting the input into such space.

 Ranked #1 on Image Denoising on SIDD (SSIM (sRGB) metric)

Image Denoising SSIM

Practical Deep Raw Image Denoising on Mobile Devices

1 code implementation ECCV 2020 Yuzhi Wang, Haibin Huang, Qin Xu, Jiaming Liu, Yiqun Liu, Jue Wang

Deep learning-based image denoising approaches have been extensively studied in recent years, prevailing in many public benchmark datasets.

Efficient Neural Network Image Denoising

Arbitrary Video Style Transfer via Multi-Channel Correlation

no code implementations17 Sep 2020 Yingying Deng, Fan Tang, Wei-Ming Dong, Haibin Huang, Chongyang Ma, Changsheng Xu

Towards this end, we propose Multi-Channel Correction network (MCCNet), which can be trained to fuse the exemplar style features and input content features for efficient style transfer while naturally maintaining the coherence of input videos.

Style Transfer Video Style Transfer

SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning

1 code implementation6 Dec 2019 Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van Den Broeck, Stefano Soatto

To learn this representation, we train a squeeze network to drive using annotations for the side task as input.

Semantic Segmentation

Disentangled Image Matting

no code implementations ICCV 2019 Shaofan Cai, Xiaoshuai Zhang, Haoqiang Fan, Haibin Huang, Jiangyu Liu, Jiaming Liu, Jiaying Liu, Jue Wang, Jian Sun

Most previous image matting methods require a roughly-specificed trimap as input, and estimate fractional alpha values for all pixels that are in the unknown region of the trimap.

Image Matting

Semi-supervised Skin Detection by Network with Mutual Guidance

no code implementations ICCV 2019 Yi He, Jiayuan Shi, Chuan Wang, Haibin Huang, Jiaming Liu, Guanbin Li, Risheng Liu, Jue Wang

In this paper we present a new data-driven method for robust skin detection from a single human portrait image.

Frame-Recurrent Video Inpainting by Robust Optical Flow Inference

no code implementations8 May 2019 Yifan Ding, Chuan Wang, Haibin Huang, Jiaming Liu, Jue Wang, Liqiang Wang

Compared with image inpainting, performing this task on video presents new challenges such as how to preserving temporal consistency and spatial details, as well as how to handle arbitrary input video size and length fast and efficiently.

Image Inpainting Optical Flow Estimation +1

When AWGN-based Denoiser Meets Real Noises

2 code implementations6 Apr 2019 Yuqian Zhou, Jianbo Jiao, Haibin Huang, Yang Wang, Jue Wang, Honghui Shi, Thomas Huang

In this paper, we propose a novel approach to boost the performance of a real image denoiser which is trained only with synthetic pixel-independent noise data dominated by AWGN.

Denoising

GIF2Video: Color Dequantization and Temporal Interpolation of GIF images

no code implementations CVPR 2019 Yang Wang, Haibin Huang, Chuan Wang, Tong He, Jue Wang, Minh Hoai

In this paper, we propose GIF2Video, the first learning-based method for enhancing the visual quality of GIFs in the wild.

Quantization

Gourmet Photography Dataset for Aesthetic Assessment of Food Images

1 code implementation SIGGRAPH Asia 2018 2018 Kekai Sheng, Wei-Ming Dong, Haibin Huang, Chongyang Ma, Bao-Gang Hu

In this study, we present the Gourmet Photography Dataset (GPD), which is the first large-scale dataset for aesthetic assessment of food photographs.

Deep Part Induction from Articulated Object Pairs

1 code implementation19 Sep 2018 Li Yi, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, Leonidas Guibas

In this paper, we explore how the observation of different articulation states provides evidence for part structure and motion of 3D objects.

Object

Video Inpainting by Jointly Learning Temporal Structure and Spatial Details

no code implementations22 Jun 2018 Chuan Wang, Haibin Huang, Xiaoguang Han, Jue Wang

We present a new data-driven video inpainting method for recovering missing regions of video frames.

Video Inpainting

High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference

no code implementations ICCV 2017 Xiaoguang Han, Zhen Li, Haibin Huang, Evangelos Kalogerakis, Yizhou Yu

Our method is based on a new deep learning architecture consisting of two sub-networks: a global structure inference network and a local geometry refinement network.

Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks

no code implementations CVPR 2017 Amir Arsalan Soltani, Haibin Huang, Jiajun Wu, Tejas D. Kulkarni, Joshua B. Tenenbaum

We take an alternative approach: learning a generative model over multi-view depth maps or their corresponding silhouettes, and using a deterministic rendering function to produce 3D shapes from these images.

Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks

no code implementations14 Jun 2017 Haibin Huang, Evangelos Kalogerakis, Siddhartha Chaudhuri, Duygu Ceylan, Vladimir G. Kim, Ersin Yumer

We present a new local descriptor for 3D shapes, directly applicable to a wide range of shape analysis problems such as point correspondences, semantic segmentation, affordance prediction, and shape-to-scan matching.

Semantic Segmentation

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