Search Results for author: Nian Liu

Found 43 papers, 26 papers with code

Predicting Eye Fixations Using Convolutional Neural Networks

no code implementations CVPR 2015 Nian Liu, Junwei Han, Dingwen Zhang, Shifeng Wen, Tianming Liu

It is believed that eye movements in free-viewing of natural scenes are directed by both bottom-up visual saliency and top-down visual factors.

DHSNet: Deep Hierarchical Saliency Network for Salient Object Detection

no code implementations CVPR 2016 Nian Liu, Junwei Han

Then a novel hierarchical recurrent convolutional neural network (HRCNN) is adopted to further hierarchically and progressively refine the details of saliency maps step by step via integrating local context information.

Ranked #17 on RGB Salient Object Detection on DUTS-TE (max F-measure metric)

Object object-detection +2

A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection

2 code implementations6 Oct 2016 Nian Liu, Junwei Han

Furthermore, the proposed DSCLSTM model can significantly boost the saliency detection performance by incorporating both global spatial interconnections and scene context modulation, which may uncover novel inspirations for studies on them in computational saliency models.

Saliency Detection

PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection

2 code implementations15 Dec 2018 Nian Liu, Junwei Han, Ming-Hsuan Yang

We propose three specific formulations of the PiCANet via embedding the pixel-wise contextual attention mechanism into the pooling and convolution operations with attending to global or local contexts.

object-detection RGB Salient Object Detection +3

Online Multi-Object Tracking with Dual Matching Attention Networks

1 code implementation ECCV 2018 Ji Zhu, Hua Yang, Nian Liu, Minyoung Kim, Wenjun Zhang, Ming-Hsuan Yang

In this paper, we propose an online Multi-Object Tracking (MOT) approach which integrates the merits of single object tracking and data association methods in a unified framework to handle noisy detections and frequent interactions between targets.

Multi-Object Tracking Object +1

Learning Selective Self-Mutual Attention for RGB-D Saliency Detection

1 code implementation CVPR 2020 Nian Liu, Ni Zhang, Junwei Han

Considering the reliability of the other modality's attention, we further propose a selection attention to weight the newly added attention term.

RGB-D Salient Object Detection Saliency Detection

Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection

1 code implementation12 Oct 2020 Nian Liu, Ni Zhang, Ling Shao, Junwei Han

Early fusion and the result fusion schemes fuse RGB and depth information at the input and output stages, respectively, hence incur the problem of distribution gap or information loss.

object-detection RGB-D Salient Object Detection +2

Weakly Supervised Video Salient Object Detection

1 code implementation CVPR 2021 Wangbo Zhao, Jing Zhang, Long Li, Nick Barnes, Nian Liu, Junwei Han

Significant performance improvement has been achieved for fully-supervised video salient object detection with the pixel-wise labeled training datasets, which are time-consuming and expensive to obtain.

Object object-detection +4

Lorentzian Graph Convolutional Networks

no code implementations15 Apr 2021 Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song

We also find that the performance of some hyperbolic GCNs can be improved by simply replacing the graph operations with those we defined in this paper.

Visual Saliency Transformer

1 code implementation ICCV 2021 Nian Liu, Ni Zhang, Kaiyuan Wan, Ling Shao, Junwei Han

We also develop a token-based multi-task decoder to simultaneously perform saliency and boundary detection by introducing task-related tokens and a novel patch-task-attention mechanism.

Boundary Detection object-detection +4

Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning

3 code implementations19 May 2021 Xiao Wang, Nian Liu, Hui Han, Chuan Shi

Then the cross-view contrastive learning, as well as a view mask mechanism, is proposed, which is able to extract the positive and negative embeddings from two views.

Contrastive Learning

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

2 code implementations26 May 2021 Yujia Sun, Geng Chen, Tao Zhou, Yi Zhang, Nian Liu

Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings.

Object object-detection +1

Instance-Level Relative Saliency Ranking with Graph Reasoning

no code implementations8 Jul 2021 Nian Liu, Long Li, Wangbo Zhao, Junwei Han, Ling Shao

Conventional salient object detection models cannot differentiate the importance of different salient objects.

Image Retargeting object-detection +2

Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection

1 code implementation ICCV 2021 Ni Zhang, Junwei Han, Nian Liu, Ling Shao

In this paper, we propose a novel consensus-aware dynamic convolution model to explicitly and effectively perform the "summarize and search" process.

Co-Salient Object Detection

Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance

1 code implementation2 Oct 2021 Nian Liu, Wangbo Zhao, Dingwen Zhang, Junwei Han, Ling Shao

On the other hand, instead of processing the twokinds of data separately, we build a novel dual graph modelto guide the focal stack fusion process using all-focus pat-terns.

Graph Learning Saliency Detection

Compact Graph Structure Learning via Mutual Information Compression

2 code implementations14 Jan 2022 Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

Furthermore, we maintain the performance of estimated views and the final view and reduce the mutual information of every two views.

Graph structure learning

Debiased Graph Neural Networks with Agnostic Label Selection Bias

no code implementations19 Jan 2022 Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang

Then to remove the bias in GNN estimation, we propose a novel Debiased Graph Neural Networks (DGNN) with a differentiated decorrelation regularizer.

Selection bias

Learning Non-target Knowledge for Few-shot Semantic Segmentation

1 code implementation CVPR 2022 Yuanwei Liu, Nian Liu, Qinglong Cao, Xiwen Yao, Junwei Han, Ling Shao

Then, a BG Eliminating Module and a DO Eliminating Module are proposed to successively filter out the BG and DO information from the query feature, based on which we can obtain a BG and DO-free target object segmentation result.

Contrastive Learning Few-Shot Semantic Segmentation +3

Structured Attention Composition for Temporal Action Localization

2 code implementations20 May 2022 Le Yang, Junwei Han, Tao Zhao, Nian Liu, Dingwen Zhang

To tackle this issue, we make an early effort to study temporal action localization from the perspective of multi-modality feature learning, based on the observation that different actions exhibit specific preferences to appearance or motion modality.

Action Detection Temporal Action Localization

Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum

1 code implementation5 Oct 2022 Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei

Then we theoretically prove that GCL is able to learn the invariance information by contrastive invariance theorem, together with our GAME rule, for the first time, we uncover that the learned representations by GCL essentially encode the low-frequency information, which explains why GCL works.

Contrastive Learning

Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation

1 code implementation13 Oct 2022 Yuanwei Liu, Nian Liu, Xiwen Yao, Junwei Han

To solve this problem, we are the first to introduce an intermediate prototype for mining both deterministic category information from the support and adaptive category knowledge from the query.

Few-Shot Semantic Segmentation Semantic Segmentation

A Deep Learning Approach to Generating Photospheric Vector Magnetograms of Solar Active Regions for SOHO/MDI Using SDO/HMI and BBSO Data

no code implementations4 Nov 2022 Haodi Jiang, Qin Li, Zhihang Hu, Nian Liu, Yasser Abduallah, Ju Jing, Genwei Zhang, Yan Xu, Wynne Hsu, Jason T. L. Wang, Haimin Wang

We propose a new deep learning method, named MagNet, to learn from combined LOS magnetograms, Bx and By taken by SDO/HMI along with H-alpha observations collected by the Big Bear Solar Observatory (BBSO), and to generate vector components Bx' and By', which would form vector magnetograms with observed LOS data.

Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt

no code implementations CVPR 2023 Hao Li, Dingwen Zhang, Nian Liu, Lechao Cheng, Yalun Dai, Chao Zhang, Xinggang Wang, Junwei Han

Inspired by the recent success of the Prompting technique, we introduce a new pre-training method that boosts QEIS models by giving Saliency Prompt for queries/kernels.

Instance Segmentation Semantic Segmentation +1

A Latent Fingerprint in the Wild Database

no code implementations3 Apr 2023 Xinwei Liu, Kiran Raja, Renfang Wang, Hong Qiu, Hucheng Wu, Dechao Sun, Qiguang Zheng, Nian Liu, Xiaoxia Wang, Gehang Huang, Raghavendra Ramachandra, Christoph Busch

Further, existing databases for latent fingerprint recognition do not have a large number of unique subjects/fingerprint instances or do not provide ground truth/reference fingerprint images to conduct a cross-comparison against the latent.

Benchmarking

Hierarchical Contrastive Learning Enhanced Heterogeneous Graph Neural Network

no code implementations24 Apr 2023 Nian Liu, Xiao Wang, Hui Han, Chuan Shi

Specifically, two views of a HIN (network schema and meta-path views) are proposed to learn node embeddings, so as to capture both of local and high-order structures simultaneously.

Contrastive Learning

Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection

1 code implementation CVPR 2023 Long Li, Junwei Han, Ni Zhang, Nian Liu, Salman Khan, Hisham Cholakkal, Rao Muhammad Anwer, Fahad Shahbaz Khan

Then, we use two types of pre-defined tokens to mine co-saliency and background information via our proposed contrast-induced pixel-to-token correlation and co-saliency token-to-token correlation modules.

Computational Efficiency Co-Salient Object Detection +3

Heterogeneous Value Alignment Evaluation for Large Language Models

2 code implementations26 May 2023 Zhaowei Zhang, Ceyao Zhang, Nian Liu, Siyuan Qi, Ziqi Rong, Song-Chun Zhu, Shuguang Cui, Yaodong Yang

We conduct evaluations with new auto-metric \textit{value rationality} to represent the ability of LLMs to align with specific values.

Attribute

CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance Segmentation

1 code implementation16 Jul 2023 Jialun Pei, Tao Jiang, He Tang, Nian Liu, Yueming Jin, Deng-Ping Fan, Pheng-Ann Heng

We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet.

Instance Segmentation Semantic Segmentation

Provable Training for Graph Contrastive Learning

1 code implementation NeurIPS 2023 Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi

To this end, we propose the PrOvable Training (POT) for GCL, which regularizes the training of GCL to encode node embeddings that follows the GCL principle better.

Contrastive Learning

VST++: Efficient and Stronger Visual Saliency Transformer

no code implementations18 Oct 2023 Nian Liu, Ziyang Luo, Ni Zhang, Junwei Han

Our previous work, the Visual Saliency Transformer (VST), addressed this constraint from a transformer-based sequence-to-sequence perspective, to unify RGB and RGB-D SOD.

object-detection Object Detection +1

CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents

1 code implementation19 Jan 2024 Siyuan Qi, Shuo Chen, Yexin Li, Xiangyu Kong, Junqi Wang, Bangcheng Yang, Pring Wong, Yifan Zhong, Xiaoyuan Zhang, Zhaowei Zhang, Nian Liu, Wei Wang, Yaodong Yang, Song-Chun Zhu

Within CivRealm, we provide interfaces for two typical agent types: tensor-based agents that focus on learning, and language-based agents that emphasize reasoning.

Decision Making

V2VSSC: A 3D Semantic Scene Completion Benchmark for Perception with Vehicle to Vehicle Communication

no code implementations7 Feb 2024 Yuanfang Zhang, Junxuan Li, Kaiqing Luo, Yiying Yang, Jiayi Han, Nian Liu, Denghui Qin, Peng Han, Chengpei Xu

Extensive experiments demonstrate that by leveraging V2V communication, the SSC performance can be increased by 8. 3% on geometric metric IoU and 6. 0% mIOU.

3D Semantic Scene Completion Autonomous Vehicles

TransGOP: Transformer-Based Gaze Object Prediction

no code implementations21 Feb 2024 Binglu Wang, Chenxi Guo, Yang Jin, Haisheng Xia, Nian Liu

Gaze object prediction aims to predict the location and category of the object that is watched by a human.

Gaze Estimation Object +2

Learning Invariant Representations of Graph Neural Networks via Cluster Generalization

1 code implementation NeurIPS 2023 Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi

To address this challenge, we propose the Cluster Information Transfer (CIT) mechanism (Code available at https://github. com/BUPT-GAMMA/CITGNN), which can learn invariant representations for GNNs, thereby improving their generalization ability to various and unknown test graphs with structure shift.

AnySkill: Learning Open-Vocabulary Physical Skill for Interactive Agents

no code implementations19 Mar 2024 Jieming Cui, Tengyu Liu, Nian Liu, Yaodong Yang, Yixin Zhu, Siyuan Huang

Traditional approaches in physics-based motion generation, centered around imitation learning and reward shaping, often struggle to adapt to new scenarios.

Imitation Learning

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