Search Results for author: Xiaojuan Qi

Found 105 papers, 66 papers with code

Memory Selection Network for Video Propagation

no code implementations ECCV 2020 Ruizheng Wu, Huaijia Lin, Xiaojuan Qi, Jiaya Jia

Video propagation is a fundamental problem in video processing where guidance frame predictions are propagated to guide predictions of the target frame.

Colorization Semantic Segmentation +3

CN: Channel Normalization For Point Cloud Recognition

no code implementations ECCV 2020 Zetong Yang, Yanan sun, Shu Liu, Xiaojuan Qi, Jiaya Jia

In 3D recognition, to fuse multi-scale structure information, existing methods apply hierarchical frameworks stacked by multiple fusion layers for integrating current relative locations with structure information from the previous level.

Classes Are Not Equal: An Empirical Study on Image Recognition Fairness

1 code implementation28 Feb 2024 Jiequan Cui, Beier Zhu, Xin Wen, Xiaojuan Qi, Bei Yu, Hanwang Zhang

Second, with the proposed concept of Model Prediction Bias, we investigate the origins of problematic representation during optimization.

Data Augmentation Fairness +2

Spec-Gaussian: Anisotropic View-Dependent Appearance for 3D Gaussian Splatting

no code implementations24 Feb 2024 ZiYi Yang, Xinyu Gao, Yangtian Sun, Yihua Huang, Xiaoyang Lyu, Wen Zhou, Shaohui Jiao, Xiaojuan Qi, Xiaogang Jin

The recent advancements in 3D Gaussian splatting (3D-GS) have not only facilitated real-time rendering through modern GPU rasterization pipelines but have also attained state-of-the-art rendering quality.

Debiasing Text-to-Image Diffusion Models

no code implementations22 Feb 2024 Ruifei He, Chuhui Xue, Haoru Tan, Wenqing Zhang, Yingchen Yu, Song Bai, Xiaojuan Qi

Despite its simplicity, we show that IDA shows efficiency and fast convergence in resolving the social bias in TTI diffusion models.

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

1 code implementation6 Feb 2024 Wei Huang, Yangdong Liu, Haotong Qin, Ying Li, Shiming Zhang, Xianglong Liu, Michele Magno, Xiaojuan Qi

Pretrained large language models (LLMs) exhibit exceptional general language processing capabilities but come with significant demands on memory and computational resources.

Binarization Quantization

V-IRL: Grounding Virtual Intelligence in Real Life

1 code implementation5 Feb 2024 Jihan Yang, Runyu Ding, Ellis Brown, Xiaojuan Qi, Saining Xie

There is a sensory gulf between the Earth that humans inhabit and the digital realms in which modern AI agents are created.

Decision Making

GO-NeRF: Generating Virtual Objects in Neural Radiance Fields

no code implementations11 Jan 2024 Peng Dai, Feitong Tan, Xin Yu, yinda zhang, Xiaojuan Qi

To this end, we propose a new method, GO-NeRF, capable of utilizing scene context for high-quality and harmonious 3D object generation within an existing NeRF.

Object

UniDream: Unifying Diffusion Priors for Relightable Text-to-3D Generation

no code implementations14 Dec 2023 Zexiang Liu, Yangguang Li, Youtian Lin, Xin Yu, Sida Peng, Yan-Pei Cao, Xiaojuan Qi, Xiaoshui Huang, Ding Liang, Wanli Ouyang

Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D objects.

Text to 3D

Random resistive memory-based deep extreme point learning machine for unified visual processing

no code implementations14 Dec 2023 Shaocong Wang, Yizhao Gao, Yi Li, Woyu Zhang, Yifei Yu, Bo wang, Ning Lin, Hegan Chen, Yue Zhang, Yang Jiang, Dingchen Wang, Jia Chen, Peng Dai, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Xiaoxin Xu, Hayden So, Zhongrui Wang, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks.

SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

1 code implementation4 Dec 2023 Yi-Hua Huang, Yang-tian Sun, ZiYi Yang, Xiaoyang Lyu, Yan-Pei Cao, Xiaojuan Qi

During learning, the location and number of control points are adaptively adjusted to accommodate varying motion complexities in different regions, and an ARAP loss following the principle of as rigid as possible is developed to enforce spatial continuity and local rigidity of learned motions.

Novel View Synthesis

Pruning random resistive memory for optimizing analogue AI

no code implementations13 Nov 2023 Yi Li, Songqi Wang, Yaping Zhao, Shaocong Wang, Woyu Zhang, Yangu He, Ning Lin, Binbin Cui, Xi Chen, Shiming Zhang, Hao Jiang, Peng Lin, Xumeng Zhang, Xiaojuan Qi, Zhongrui Wang, Xiaoxin Xu, Dashan Shang, Qi Liu, Kwang-Ting Cheng, Ming Liu

Here, we report a universal solution, software-hardware co-design using structural plasticity-inspired edge pruning to optimize the topology of a randomly weighted analogue resistive memory neural network.

Audio Classification Image Segmentation +1

Text-to-3D with Classifier Score Distillation

no code implementations30 Oct 2023 Xin Yu, Yuan-Chen Guo, Yangguang Li, Ding Liang, Song-Hai Zhang, Xiaojuan Qi

In this paper, we re-evaluate the role of classifier-free guidance in score distillation and discover a surprising finding: the guidance alone is enough for effective text-to-3D generation tasks.

Text to 3D Texture Synthesis

SpikeMOT: Event-based Multi-Object Tracking with Sparse Motion Features

no code implementations29 Sep 2023 Song Wang, Zhu Wang, Can Li, Xiaojuan Qi, Hayden Kwok-Hay So

In comparison to conventional RGB cameras, the superior temporal resolution of event cameras allows them to capture rich information between frames, making them prime candidates for object tracking.

Multi-Object Tracking Object

Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video

1 code implementation ICCV 2023 Xiuzhe Wu, Pengfei Hu, Yang Wu, Xiaoyang Lyu, Yan-Pei Cao, Ying Shan, Wenming Yang, Zhongqian Sun, Xiaojuan Qi

Therefore, directly learning a mapping function from speech to the entire head image is prone to ambiguity, particularly when using a short video for training.

Image Generation

Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding

no code implementations1 Aug 2023 Runyu Ding, Jihan Yang, Chuhui Xue, Wenqing Zhang, Song Bai, Xiaojuan Qi

To address this challenge, we propose to harness pre-trained vision-language (VL) foundation models that encode extensive knowledge from image-text pairs to generate captions for multi-view images of 3D scenes.

3D Open-Vocabulary Instance Segmentation Instance Segmentation +4

MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds

1 code implementation CVPR 2023 Jiahui Liu, Chirui Chang, Jianhui Liu, Xiaoyang Wu, Lan Ma, Xiaojuan Qi

Unlike the single-scan-based semantic segmentation task, this task requires distinguishing the motion states of points in addition to their semantic categories.

3D Semantic Segmentation Representation Learning +1

Decoupled Kullback-Leibler Divergence Loss

4 code implementations23 May 2023 Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang

In this paper, we delve deeper into the Kullback-Leibler (KL) Divergence loss and observe that it is equivalent to the Doupled Kullback-Leibler (DKL) Divergence loss that consists of 1) a weighted Mean Square Error (wMSE) loss and 2) a Cross-Entropy loss incorporating soft labels.

Adversarial Defense Adversarial Robustness +1

RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding

no code implementations3 Apr 2023 Jihan Yang, Runyu Ding, Zhe Wang, Xiaojuan Qi

Existing 3D scene understanding tasks have achieved high performance on close-set benchmarks but fail to handle novel categories in real-world applications.

Contrastive Learning Instance Segmentation +2

Context-Aware Transformer for 3D Point Cloud Automatic Annotation

no code implementations27 Mar 2023 Xiaoyan Qian, Chang Liu, Xiaojuan Qi, Siew-Chong Tan, Edmund Lam, Ngai Wong

3D automatic annotation has received increased attention since manually annotating 3D point clouds is laborious.

Object

You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene Understanding

1 code implementation26 Mar 2023 Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu

3D scene understanding, e. g., point cloud semantic and instance segmentation, often requires large-scale annotated training data, but clearly, point-wise labels are too tedious to prepare.

3D Instance Segmentation Pseudo Label +4

DreamStone: Image as Stepping Stone for Text-Guided 3D Shape Generation

2 code implementations24 Mar 2023 Zhengzhe Liu, Peng Dai, Ruihui Li, Xiaojuan Qi, Chi-Wing Fu

The core of our approach is a two-stage feature-space alignment strategy that leverages a pre-trained single-view reconstruction (SVR) model to map CLIP features to shapes: to begin with, map the CLIP image feature to the detail-rich 3D shape space of the SVR model, then map the CLIP text feature to the 3D shape space through encouraging the CLIP-consistency between rendered images and the input text.

3D Shape Generation

IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformation

1 code implementation ICCV 2023 Jianhui Liu, Yukang Chen, Xiaoqing Ye, Xiaojuan Qi

Category-level 6D pose estimation aims to predict the poses and sizes of unseen objects from a specific category.

6D Pose Estimation

Learning Context-aware Classifier for Semantic Segmentation

2 code implementations21 Mar 2023 Zhuotao Tian, Jiequan Cui, Li Jiang, Xiaojuan Qi, Xin Lai, Yixin Chen, Shu Liu, Jiaya Jia

Semantic segmentation is still a challenging task for parsing diverse contexts in different scenes, thus the fixed classifier might not be able to well address varying feature distributions during testing.

Segmentation Semantic Segmentation

Learning a Room with the Occ-SDF Hybrid: Signed Distance Function Mingled with Occupancy Aids Scene Representation

1 code implementation ICCV 2023 Xiaoyang Lyu, Peng Dai, Zizhang Li, Dongyu Yan, Yi Lin, Yifan Peng, Xiaojuan Qi

We found that the color rendering loss results in optimization bias against low-intensity areas, causing gradient vanishing and leaving these areas unoptimized.

Neural Rendering Surface Reconstruction

Understanding Imbalanced Semantic Segmentation Through Neural Collapse

2 code implementations CVPR 2023 Zhisheng Zhong, Jiequan Cui, Yibo Yang, Xiaoyang Wu, Xiaojuan Qi, Xiangyu Zhang, Jiaya Jia

Based on our empirical and theoretical analysis, we point out that semantic segmentation naturally brings contextual correlation and imbalanced distribution among classes, which breaks the equiangular and maximally separated structure of neural collapse for both feature centers and classifiers.

3D Semantic Segmentation Segmentation

Command-Driven Articulated Object Understanding and Manipulation

no code implementations CVPR 2023 Ruihang Chu, Zhengzhe Liu, Xiaoqing Ye, Xiao Tan, Xiaojuan Qi, Chi-Wing Fu, Jiaya Jia

The key of Cart is to utilize the prediction of object structures to connect visual observations with user commands for effective manipulations.

motion prediction Object

Vertical Layering of Quantized Neural Networks for Heterogeneous Inference

no code implementations10 Dec 2022 Hai Wu, Ruifei He, Haoru Tan, Xiaojuan Qi, Kaibin Huang

Experiments show that the proposed vertical-layered representation and developed once QAT scheme are effective in embodying multiple quantized networks into a single one and allow one-time training, and it delivers comparable performance as that of quantized models tailored to any specific bit-width.

Quantization

SL3D: Self-supervised-Self-labeled 3D Recognition

1 code implementation30 Oct 2022 Fernando Julio Cendra, Lan Ma, Jiajun Shen, Xiaojuan Qi

SL3D is a generic framework and can be applied to solve different 3D recognition tasks, including classification, object detection, and semantic segmentation.

Clustering Object +5

Is synthetic data from generative models ready for image recognition?

1 code implementation14 Oct 2022 Ruifei He, Shuyang Sun, Xin Yu, Chuhui Xue, Wenqing Zhang, Philip Torr, Song Bai, Xiaojuan Qi

Recent text-to-image generation models have shown promising results in generating high-fidelity photo-realistic images.

Text-to-Image Generation Transfer Learning

Prototypical VoteNet for Few-Shot 3D Point Cloud Object Detection

1 code implementation11 Oct 2022 Shizhen Zhao, Xiaojuan Qi

Most existing 3D point cloud object detection approaches heavily rely on large amounts of labeled training data.

Object object-detection +2

In-situ Model Downloading to Realize Versatile Edge AI in 6G Mobile Networks

no code implementations7 Oct 2022 Kaibin Huang, Hai Wu, Zhiyan Liu, Xiaojuan Qi

We further propose a virtualized 6G network architecture customized for deploying in-situ model downloading with the key feature of a three-tier (edge, local, and central) AI library.

Spatial Pruned Sparse Convolution for Efficient 3D Object Detection

no code implementations28 Sep 2022 Jianhui Liu, Yukang Chen, Xiaoqing Ye, Zhuotao Tian, Xiao Tan, Xiaojuan Qi

3D scenes are dominated by a large number of background points, which is redundant for the detection task that mainly needs to focus on foreground objects.

3D Object Detection Object +1

Rethinking Resolution in the Context of Efficient Video Recognition

1 code implementation26 Sep 2022 Chuofan Ma, Qiushan Guo, Yi Jiang, Zehuan Yuan, Ping Luo, Xiaojuan Qi

Our key finding is that the major cause of degradation is not information loss in the down-sampling process, but rather the mismatch between network architecture and input scale.

Knowledge Distillation Video Recognition

ISS: Image as Stepping Stone for Text-Guided 3D Shape Generation

2 code implementations9 Sep 2022 Zhengzhe Liu, Peng Dai, Ruihui Li, Xiaojuan Qi, Chi-Wing Fu

Text-guided 3D shape generation remains challenging due to the absence of large paired text-shape data, the substantial semantic gap between these two modalities, and the structural complexity of 3D shapes.

3D Shape Generation

Multimodal Transformer for Automatic 3D Annotation and Object Detection

1 code implementation20 Jul 2022 Chang Liu, Xiaoyan Qian, Binxiao Huang, Xiaojuan Qi, Edmund Lam, Siew-Chong Tan, Ngai Wong

By enriching the sparse point clouds, our method achieves 4. 48\% and 4. 03\% better 3D AP on KITTI moderate and hard samples, respectively, versus the state-of-the-art autolabeler.

3D Object Detection Object +1

Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

1 code implementation20 Jul 2022 Xin Yu, Peng Dai, Wenbo Li, Lan Ma, Jiajun Shen, Jia Li, Xiaojuan Qi

With the rapid development of mobile devices, modern widely-used mobile phones typically allow users to capture 4K resolution (i. e., ultra-high-definition) images.

Image Enhancement Image Restoration +1

Unifying Voxel-based Representation with Transformer for 3D Object Detection

1 code implementation1 Jun 2022 Yanwei Li, Yilun Chen, Xiaojuan Qi, Zeming Li, Jian Sun, Jiaya Jia

To this end, the modality-specific space is first designed to represent different inputs in the voxel feature space.

3D Object Detection Object +3

Voxel Field Fusion for 3D Object Detection

1 code implementation CVPR 2022 Yanwei Li, Xiaojuan Qi, Yukang Chen, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In this work, we present a conceptually simple yet effective framework for cross-modality 3D object detection, named voxel field fusion.

3D Object Detection Data Augmentation +2

Self-Supervised Visual Representation Learning with Semantic Grouping

1 code implementation30 May 2022 Xin Wen, Bingchen Zhao, Anlin Zheng, Xiangyu Zhang, Xiaojuan Qi

The semantic grouping is performed by assigning pixels to a set of learnable prototypes, which can adapt to each sample by attentive pooling over the feature and form new slots.

Contrastive Learning Instance Segmentation +6

Towards Efficient 3D Object Detection with Knowledge Distillation

1 code implementation30 May 2022 Jihan Yang, Shaoshuai Shi, Runyu Ding, Zhe Wang, Xiaojuan Qi

Then, we build a benchmark to assess existing KD methods developed in the 2D domain for 3D object detection upon six well-constructed teacher-student pairs.

3D Object Detection Knowledge Distillation +3

Video Demoireing with Relation-Based Temporal Consistency

1 code implementation CVPR 2022 Peng Dai, Xin Yu, Lan Ma, Baoheng Zhang, Jia Li, Wenbo Li, Jiajun Shen, Xiaojuan Qi

Moire patterns, appearing as color distortions, severely degrade image and video qualities when filming a screen with digital cameras.

Relation

MAP-Gen: An Automated 3D-Box Annotation Flow with Multimodal Attention Point Generator

no code implementations29 Mar 2022 Chang Liu, Xiaoyan Qian, Xiaojuan Qi, Edmund Y. Lam, Siew-Chong Tan, Ngai Wong

While a few previous studies tried to automatically generate 3D bounding boxes from weak labels such as 2D boxes, the quality is sub-optimal compared to human annotators.

object-detection Object Detection

Stratified Transformer for 3D Point Cloud Segmentation

4 code implementations CVPR 2022 Xin Lai, Jianhui Liu, Li Jiang, LiWei Wang, Hengshuang Zhao, Shu Liu, Xiaojuan Qi, Jiaya Jia

In this paper, we propose Stratified Transformer that is able to capture long-range contexts and demonstrates strong generalization ability and high performance.

Point Cloud Segmentation Position +1

HINT: Hierarchical Neuron Concept Explainer

1 code implementation CVPR 2022 Andong Wang, Wei-Ning Lee, Xiaojuan Qi

To this end, we propose HIerarchical Neuron concepT explainer (HINT) to effectively build bidirectional associations between neurons and hierarchical concepts in a low-cost and scalable manner.

Weakly-Supervised Object Localization

Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking

2 code implementations CVPR 2020 Jin Gao, Yan Lu, Xiaojuan Qi, Yutong Kou, Bing Li, Liang Li, Shan Yu, Weiming Hu

In this paper, we propose a simple yet effective recursive least-squares estimator-aided online learning approach for few-shot online adaptation without requiring offline training.

Continual Learning One-Shot Learning +1

Slot-VPS: Object-centric Representation Learning for Video Panoptic Segmentation

no code implementations CVPR 2022 Yi Zhou, HUI ZHANG, Hana Lee, Shuyang Sun, Pingjun Li, Yangguang Zhu, ByungIn Yoo, Xiaojuan Qi, Jae-Joon Han

We encode all panoptic entities in a video, including both foreground instances and background semantics, with a unified representation called panoptic slots.

Object Representation Learning +1

Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision

1 code implementation17 Aug 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, Yukang Chen, Lu Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In particular, Panoptic FCN encodes each object instance or stuff category with the proposed kernel generator and produces the prediction by convolving the high-resolution feature directly.

Panoptic Segmentation Segmentation +1

ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection

no code implementations15 Aug 2021 Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, Xiaojuan Qi

These specific designs enable the detector to be trained on meticulously refined pseudo labeled target data with denoised training signals, and thus effectively facilitate adapting an object detector to a target domain without requiring annotations.

3D Object Detection Data Augmentation +5

Multilevel Knowledge Transfer for Cross-Domain Object Detection

no code implementations2 Aug 2021 Botos Csaba, Xiaojuan Qi, Arslan Chaudhry, Puneet Dokania, Philip Torr

The key ingredients to our approach are -- (a) mapping the source to the target domain on pixel-level; (b) training a teacher network on the mapped source and the unannotated target domain using adversarial feature alignment; and (c) finally training a student network using the pseudo-labels obtained from the teacher.

Object object-detection +2

Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation

1 code implementation ICCV 2021 Ruifei He, Jihan Yang, Xiaojuan Qi

In this paper, we present a simple and yet effective Distribution Alignment and Random Sampling (DARS) method to produce unbiased pseudo labels that match the true class distribution estimated from the labeled data.

Data Augmentation Segmentation +1

One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation

2 code implementations CVPR 2021 Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu

Point cloud semantic segmentation often requires largescale annotated training data, but clearly, point-wise labels are too tedious to prepare.

3D Semantic Segmentation Relation Network +1

3D-to-2D Distillation for Indoor Scene Parsing

1 code implementation CVPR 2021 Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu

First, we distill 3D knowledge from a pretrained 3D network to supervise a 2D network to learn simulated 3D features from 2D features during the training, so the 2D network can infer without requiring 3D data.

Scene Parsing Semantic Parsing +1

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

2 code implementations CVPR 2021 Mutian Xu, Runyu Ding, Hengshuang Zhao, Xiaojuan Qi

The key of PAConv is to construct the convolution kernel by dynamically assembling basic weight matrices stored in Weight Bank, where the coefficients of these weight matrices are self-adaptively learned from point positions through ScoreNet.

3D Point Cloud Classification Point Cloud Classification +2

AET-EFN: A Versatile Design for Static and Dynamic Event-Based Vision

no code implementations22 Mar 2021 Chang Liu, Xiaojuan Qi, Edmund Lam, Ngai Wong

The neuromorphic event cameras, which capture the optical changes of a scene, have drawn increasing attention due to their high speed and low power consumption.

Event-based vision

ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

1 code implementation CVPR 2021 Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, Xiaojuan Qi

Then, the detector is iteratively improved on the target domain by alternatively conducting two steps, which are the pseudo label updating with the developed quality-aware triplet memory bank and the model training with curriculum data augmentation.

3D Object Detection Data Augmentation +4

Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud

2 code implementations20 Dec 2020 Mutian Xu, Junhao Zhang, Zhipeng Zhou, Mingye Xu, Xiaojuan Qi, Yu Qiao

GDANet introduces Geometry-Disentangle Module to dynamically disentangle point clouds into the contour and flat part of 3D objects, respectively denoted by sharp and gentle variation components.

3D Object Classification 3D Part Segmentation +2

GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation

2 code implementations13 Dec 2020 Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia

Note that GeoNet++ is generic and can be used in other depth/normal prediction frameworks to improve the quality of 3D reconstruction and pixel-wise accuracy of depth and surface normals.

3D Reconstruction Depth Estimation +2

Fully Convolutional Networks for Panoptic Segmentation

6 code implementations CVPR 2021 Yanwei Li, Hengshuang Zhao, Xiaojuan Qi, LiWei Wang, Zeming Li, Jian Sun, Jiaya Jia

In this paper, we present a conceptually simple, strong, and efficient framework for panoptic segmentation, called Panoptic FCN.

Panoptic Segmentation Segmentation

Object-aware Feature Aggregation for Video Object Detection

no code implementations23 Oct 2020 Qichuan Geng, Hong Zhang, Na Jiang, Xiaojuan Qi, Liangjun Zhang, Zhong Zhou

As a consequence, augmenting features with such prior knowledge can effectively improve the classification and localization performance.

Object object-detection +2

Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation

1 code implementation NeurIPS 2020 Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz

To achieve this, a new word-level discriminator is proposed, which provides the generator with fine-grained training feedback at word-level, to facilitate training a lightweight generator that has a small number of parameters, but can still correctly focus on specific visual attributes of an image, and then edit them without affecting other contents that are not described in the text.

Generative Adversarial Network Image Manipulation +1

Image-to-Image Translation with Text Guidance

no code implementations12 Feb 2020 Bowen Li, Xiaojuan Qi, Philip H. S. Torr, Thomas Lukasiewicz

The goal of this paper is to embed controllable factors, i. e., natural language descriptions, into image-to-image translation with generative adversarial networks, which allows text descriptions to determine the visual attributes of synthetic images.

Image-to-Image Translation Part-Of-Speech Tagging +1

Global Texture Enhancement for Fake Face Detection in the Wild

1 code implementation CVPR 2020 Zhengzhe Liu, Xiaojuan Qi, Philip Torr

In this paper, we conduct an empirical study on fake/real faces, and have two important observations: firstly, the texture of fake faces is substantially different from real ones; secondly, global texture statistics are more robust to image editing and transferable to fake faces from different GANs and datasets.

Face Detection Fake Image Detection

Gated Path Selection Network for Semantic Segmentation

no code implementations19 Jan 2020 Qichuan Geng, Hong Zhang, Xiaojuan Qi, Ruigang Yang, Zhong Zhou, Gao Huang

Semantic segmentation is a challenging task that needs to handle large scale variations, deformations and different viewpoints.

Segmentation Semantic Segmentation

Unifying Training and Inference for Panoptic Segmentation

no code implementations CVPR 2020 Qizhu Li, Xiaojuan Qi, Philip H. S. Torr

This panoptic submodule gives rise to a novel propagation mechanism for panoptic logits and enables the network to output a coherent panoptic segmentation map for both "stuff" and "thing" classes, without any post-processing.

Panoptic Segmentation Segmentation

Few-shot Action Recognition with Permutation-invariant Attention

1 code implementation ECCV 2020 Hongguang Zhang, Li Zhang, Xiaojuan Qi, Hongdong Li, Philip H. S. Torr, Piotr Koniusz

Such encoded blocks are aggregated by permutation-invariant pooling to make our approach robust to varying action lengths and long-range temporal dependencies whose patterns are unlikely to repeat even in clips of the same class.

Few-Shot action recognition Few Shot Action Recognition +3

An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation

no code implementations18 Dec 2019 Jihan Yang, Ruijia Xu, Ruiyu Li, Xiaojuan Qi, Xiaoyong Shen, Guanbin Li, Liang Lin

In contrast to adversarial alignment, we propose to explicitly train a domain-invariant classifier by generating and defensing against pointwise feature space adversarial perturbations.

Position Segmentation +2

ManiGAN: Text-Guided Image Manipulation

3 code implementations12 Dec 2019 Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr

The goal of our paper is to semantically edit parts of an image matching a given text that describes desired attributes (e. g., texture, colour, and background), while preserving other contents that are irrelevant to the text.

Generative Adversarial Network Image Manipulation +1

Domain-invariant Stereo Matching Networks

1 code implementation ECCV 2020 Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin Wah, Philip Torr

State-of-the-art stereo matching networks have difficulties in generalizing to new unseen environments due to significant domain differences, such as color, illumination, contrast, and texture.

Stereo Matching Test

Controllable Text-to-Image Generation

2 code implementations NeurIPS 2019 Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr

In this paper, we propose a novel controllable text-to-image generative adversarial network (ControlGAN), which can effectively synthesise high-quality images and also control parts of the image generation according to natural language descriptions.

Generative Adversarial Network Text-to-Image Generation

The Liver Tumor Segmentation Benchmark (LiTS)

6 code implementations13 Jan 2019 Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.

Benchmarking Computed Tomography (CT) +3

Human Pose Estimation with Spatial Contextual Information

no code implementations7 Jan 2019 Hong Zhang, Hao Ouyang, Shu Liu, Xiaojuan Qi, Xiaoyong Shen, Ruigang Yang, Jiaya Jia

With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information.

Pose Estimation

Semantically Consistent Image Completion with Fine-grained Details

no code implementations26 Nov 2017 Pengpeng Liu, Xiaojuan Qi, Pinjia He, Yikang Li, Michael R. Lyu, Irwin King

Image completion has achieved significant progress due to advances in generative adversarial networks (GANs).

Image Inpainting

3D Graph Neural Networks for RGBD Semantic Segmentation

2 code implementations ICCV 2017 Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun

Each node in the graph corresponds to a set of points and is associated with a hidden representation vector initialized with an appearance feature extracted by a unary CNN from 2D images.

RGBD Semantic Segmentation Semantic Segmentation

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

1 code implementation21 Sep 2017 Xiaomeng Li, Hao Chen, Xiaojuan Qi, Qi Dou, Chi-Wing Fu, Pheng Ann Heng

Our method outperformed other state-of-the-arts on the segmentation results of tumors and achieved very competitive performance for liver segmentation even with a single model.

 Ranked #1 on Liver Segmentation on LiTS2017 (Dice metric)

Automatic Liver And Tumor Segmentation Image Segmentation +4

Multi-Scale Patch Aggregation (MPA) for Simultaneous Detection and Segmentation

no code implementations CVPR 2016 Shu Liu, Xiaojuan Qi, Jianping Shi, Hong Zhang, Jiaya Jia

Aiming at simultaneous detection and segmentation (SDS), we propose a proposal-free framework, which detect and segment object instances via mid-level patches.

Object Object Proposal Generation +2

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