Search Results for author: Xiaoshuai Sun

Found 27 papers, 10 papers with code

Towards Language-guided Visual Recognition via Dynamic Convolutions

no code implementations17 Oct 2021 Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Xinghao Ding, Yongjian Wu, Feiyue Huang, Yue Gao, Rongrong Ji

Based on the LaConv module, we further build the first fully language-driven convolution network, termed as LaConvNet, which can unify the visual recognition and multi-modal reasoning in one forward structure.

Question Answering Referring Expression Comprehension +1

RSTNet: Captioning With Adaptive Attention on Visual and Non-Visual Words

1 code implementation CVPR 2021 Xuying Zhang, Xiaoshuai Sun, Yunpeng Luo, Jiayi Ji, Yiyi Zhou, Yongjian Wu, Feiyue Huang, Rongrong Ji

Then, we build a BERTbased language model to extract language context and propose Adaptive-Attention (AA) module on top of a transformer decoder to adaptively measure the contribution of visual and language cues before making decisions for word prediction.

Image Captioning Language Modelling +2

Dual-Level Collaborative Transformer for Image Captioning

1 code implementation16 Jan 2021 Yunpeng Luo, Jiayi Ji, Xiaoshuai Sun, Liujuan Cao, Yongjian Wu, Feiyue Huang, Chia-Wen Lin, Rongrong Ji

Descriptive region features extracted by object detection networks have played an important role in the recent advancements of image captioning.

Image Captioning Object Detection

Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network

no code implementations13 Dec 2020 Jiayi Ji, Yunpeng Luo, Xiaoshuai Sun, Fuhai Chen, Gen Luo, Yongjian Wu, Yue Gao, Rongrong Ji

The latter contains a Global Adaptive Controller that can adaptively fuse the global information into the decoder to guide the caption generation.

Image Captioning

Fast Class-wise Updating for Online Hashing

no code implementations1 Dec 2020 Mingbao Lin, Rongrong Ji, Xiaoshuai Sun, Baochang Zhang, Feiyue Huang, Yonghong Tian, DaCheng Tao

To achieve fast online adaptivity, a class-wise updating method is developed to decompose the binary code learning and alternatively renew the hash functions in a class-wise fashion, which well addresses the burden on large amounts of training batches.

Multi-task Collaborative Network for Joint Referring Expression Comprehension and Segmentation

1 code implementation CVPR 2020 Gen Luo, Yiyi Zhou, Xiaoshuai Sun, Liujuan Cao, Chenglin Wu, Cheng Deng, Rongrong Ji

In addition, we address a key challenge in this multi-task setup, i. e., the prediction conflict, with two innovative designs namely, Consistency Energy Maximization (CEM) and Adaptive Soft Non-Located Suppression (ASNLS).

Referring Expression Comprehension Referring Expression Segmentation

A Real-time Global Inference Network for One-stage Referring Expression Comprehension

1 code implementation7 Dec 2019 Yiyi Zhou, Rongrong Ji, Gen Luo, Xiaoshuai Sun, Jinsong Su, Xinghao Ding, Chia-Wen Lin, Qi Tian

Referring Expression Comprehension (REC) is an emerging research spot in computer vision, which refers to detecting the target region in an image given an text description.

Feature Selection Referring Expression Comprehension

Variational Structured Semantic Inference for Diverse Image Captioning

no code implementations NeurIPS 2019 Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang, Yan Wang

To model these two inherent diversities in image captioning, we propose a Variational Structured Semantic Inferring model (termed VSSI-cap) executed in a novel structured encoder-inferer-decoder schema.

Image Captioning

SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation

no code implementations20 Nov 2019 Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua

In this paper, we propose a novel Semi-supervised Self-pace Adversarial Hashing method, named SSAH to solve the above problems in a unified framework.

Hadamard Codebook Based Deep Hashing

no code implementations21 Oct 2019 Shen Chen, Liujuan Cao, Mingbao Lin, Yan Wang, Xiaoshuai Sun, Chenglin Wu, Jingfei Qiu, Rongrong Ji

Specifically, we utilize an off-the-shelf algorithm to generate a binary Hadamard codebook to satisfy the requirement of bit independence and bit balance, which subsequently serves as the desired outputs of the hash functions learning.

Image Retrieval

Toward 3D Object Reconstruction from Stereo Images

1 code implementation18 Oct 2019 Haozhe Xie, Hongxun Yao, Shangchen Zhou, Shengping Zhang, Xiaoshuai Sun, Wenxiu Sun

Inferring the 3D shape of an object from an RGB image has shown impressive results, however, existing methods rely primarily on recognizing the most similar 3D model from the training set to solve the problem.

3D Object Reconstruction

Sketch-Specific Data Augmentation for Freehand Sketch Recognition

no code implementations14 Oct 2019 Ying Zheng, Hongxun Yao, Xiaoshuai Sun, Shengping Zhang, Sicheng Zhao, Fatih Porikli

Conventional methods for this task often rely on the availability of the temporal order of sketch strokes, additional cues acquired from different modalities and supervised augmentation of sketch datasets with real images, which also limit the applicability and feasibility of these methods in real scenarios.

Data Augmentation Sketch-Based Image Retrieval +1

Semantic-aware Image Deblurring

no code implementations9 Oct 2019 Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xiaoshuai Sun, Chia-Wen Lin, Jiayi Ji, Baochang Zhang, Feiyue Huang, Liujuan Cao

Specially, we propose a novel Structured-Spatial Semantic Embedding model for image deblurring (termed S3E-Deblur), which introduces a novel Structured-Spatial Semantic tree model (S3-tree) to bridge two basic tasks in computer vision: image deblurring (ImD) and image captioning (ImC).

Deblurring Image Captioning +1

Scene-based Factored Attention for Image Captioning

no code implementations7 Aug 2019 Chen Shen, Rongrong Ji, Fuhai Chen, Xiaoshuai Sun, Xiangming Li

Specifically, the proposed module first embeds the scene concepts into factored weights explicitly and attends the visual information extracted from the input image.

Image Captioning

Semi-Supervised Adversarial Monocular Depth Estimation

no code implementations6 Aug 2019 Rongrong Ji, Ke Li, Yan Wang, Xiaoshuai Sun, Feng Guo, Xiaowei Guo, Yongjian Wu, Feiyue Huang, Jiebo Luo

In this paper, we address the problem of monocular depth estimation when only a limited number of training image-depth pairs are available.

Monocular Depth Estimation

Supervised Online Hashing via Similarity Distribution Learning

no code implementations31 May 2019 Mingbao Lin, Rongrong Ji, Shen Chen, Feng Zheng, Xiaoshuai Sun, Baochang Zhang, Liujuan Cao, Guodong Guo, Feiyue Huang

In this paper, we propose to model the similarity distributions between the input data and the hashing codes, upon which a novel supervised online hashing method, dubbed as Similarity Distribution based Online Hashing (SDOH), is proposed, to keep the intrinsic semantic relationship in the produced Hamming space.

Hadamard Matrix Guided Online Hashing

1 code implementation11 May 2019 Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Shen Chen, Qi Tian

We then treat the learning of hash functions as a set of binary classification problems to fit the assigned target code.

Pix2Vox: Context-aware 3D Reconstruction from Single and Multi-view Images

5 code implementations ICCV 2019 Haozhe Xie, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, Shengping Zhang

Then, a context-aware fusion module is introduced to adaptively select high-quality reconstructions for each part (e. g., table legs) from different coarse 3D volumes to obtain a fused 3D volume.

3D Object Reconstruction 3D Reconstruction

Towards Optimal Discrete Online Hashing with Balanced Similarity

1 code implementation29 Jan 2019 Mingbao Lin, Rongrong Ji, Hong Liu, Xiaoshuai Sun, Yongjian Wu, Yunsheng Wu

In this paper, we propose a novel supervised online hashing method, termed Balanced Similarity for Online Discrete Hashing (BSODH), to solve the above problems in a unified framework.

Semantic and Contrast-Aware Saliency

no code implementations9 Nov 2018 Xiaoshuai Sun

The two pathways characterize both long-term and short-term attention cues and are integrated dynamically using maxima normalization.

Saliency Prediction

Deep Saliency Hashing

no code implementations4 Jul 2018 Sheng Jin, Hongxun Yao, Xiaoshuai Sun, Shangchen Zhou, Lei Zhang, Xian-Sheng Hua

As the core of DSaH, the saliency loss guides the attention network to mine discriminative regions from pairs of images.


GroupCap: Group-Based Image Captioning With Structured Relevance and Diversity Constraints

no code implementations CVPR 2018 Fuhai Chen, Rongrong Ji, Xiaoshuai Sun, Yongjian Wu, Jinsong Su

In offline optimization, we adopt an end-to-end formulation, which jointly trains the visual tree parser, the structured relevance and diversity constraints, as well as the LSTM based captioning model.

Image Captioning

The Effectiveness of Instance Normalization: a Strong Baseline for Single Image Dehazing

no code implementations8 May 2018 Zheng Xu, Xitong Yang, Xue Li, Xiaoshuai Sun

We propose a novel deep neural network architecture for the challenging problem of single image dehazing, which aims to recover the clear image from a degraded hazy image.

Image Dehazing Single Image Dehazing

Exploring Implicit Image Statistics for Visual Representativeness Modeling

no code implementations CVPR 2013 Xiaoshuai Sun, Xin-Jing Wang, Hongxun Yao, Lei Zhang

In this paper, we propose a computational model of visual representativeness by integrating cognitive theories of representativeness heuristics with computer vision and machine learning techniques.

Image Retrieval

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