Search Results for author: Ni Zhang

Found 7 papers, 4 papers with code

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.

Co-Salient Object Detection object-detection +1

AGAD: Adversarial Generative Anomaly Detection

no code implementations9 Apr 2023 Jian Shi, Ni Zhang

In order to address the lack of abnormal data for robust anomaly detection, we propose Adversarial Generative Anomaly Detection (AGAD), a self-contrast-based anomaly detection paradigm that learns to detect anomalies by generating \textit{contextual adversarial information} from the massive normal examples.

Semi-supervised Anomaly Detection supervised anomaly detection

Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection

no code implementations28 Feb 2023 Jian Shi, Pengyi Zhang, Ni Zhang, Hakim Ghazzai, Yehia Massoud

Interestingly, apart from the remarkable image generation abilities of diffusion models, we observed that diffusion models can dissolve image details for a given image, resulting in generalized feature representations.

Anomaly Detection Image Generation

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

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

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

Visualizing Group Dynamics based on Multiparty Meeting Understanding

no code implementations EMNLP 2018 Ni Zhang, Tongtao Zhang, Indrani Bhattacharya, Heng Ji, Rich Radke

Group discussions are usually aimed at sharing opinions, reaching consensus and making good decisions based on group knowledge.

Decision Making Opinion Mining +1

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