activity
20142026
most citedNAIS: Neural Attentive Item Similarity Model for Recommendation

592 citations · 3.2k across the 82 of their papers we have counts for

collaborators
Showing cs.CVShow all

75 papers · 1 filter

cs.CV2024★ 26 cited

BadCM: Invisible Backdoor Attack Against Cross-Modal Learning

Zheng Zhang, Xu Yuan, Lei Zhu +2

Despite remarkable successes in unimodal learning tasks, backdoor attacks against cross-modal learning are still underexplored due to the limited generalization and inferior stealt…

cs.CV2023★ 5 cited

CUCL: Codebook for Unsupervised Continual Learning

Chen Cheng, Jingkuan Song, Xiaosu Zhu +3

The focus of this study is on Unsupervised Continual Learning (UCL), as it presents an alternative to Supervised Continual Learning which needs high-quality manual labeled data. Th…

cs.CV2023★ 6 cited

Continual Referring Expression Comprehension via Dual Modular Memorization

Heng Tao Shen, Cheng Chen, Peng Wang +3

Referring Expression Comprehension (REC) aims to localize an image region of a given object described by a natural-language expression. While promising performance has been demonst…

cs.CV2023★ 14 cited

Class Gradient Projection For Continual Learning

Cheng Chen, Ji Zhang, Jingkuan Song +1

Catastrophic forgetting is one of the most critical challenges in Continual Learning (CL). Recent approaches tackle this problem by projecting the gradient update orthogonal to the…

cs.CV2023

Towards a Unified Transformer-based Framework for Scene Graph Generation and Human-object Interaction Detection

Tao He, Lianli Gao, Jingkuan Song +1

Scene graph generation (SGG) and human-object interaction (HOI) detection are two important visual tasks aiming at localising and recognising relationships between objects, and int…

cs.CV2023★ 15 cited

CHAIN: Exploring Global-Local Spatio-Temporal Information for Improved Self-Supervised Video Hashing

Rukai Wei, Yu Liu, Jingkuan Song +3

Compressing videos into binary codes can improve retrieval speed and reduce storage overhead. However, learning accurate hash codes for video retrieval can be challenging due to hi…

cs.CV2023

X-HRNet: Towards Lightweight Human Pose Estimation with Spatially Unidimensional Self-Attention

Yixuan Zhou, Xuanhan Wang, Xing Xu +2

High-resolution representation is necessary for human pose estimation to achieve high performance, and the ensuing problem is high computational complexity. In particular, predomin…

cs.CV2023★ 3 cited

Part-Aware Transformer for Generalizable Person Re-identification

Hao Ni, Yuke Li, Lianli Gao +2

Domain generalization person re-identification (DG-ReID) aims to train a model on source domains and generalize well on unseen domains. Vision Transformer usually yields better gen…

cs.CV2023★ 6 cited

Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval

Hao Li, Jingkuan Song, Lianli Gao +2

Cross-modal Retrieval methods build similarity relations between vision and language modalities by jointly learning a common representation space. However, the predictions are ofte…

cs.CV2023

DePT: Decoupled Prompt Tuning

Ji Zhang, Shihan Wu, Lianli Gao +2

This work breaks through the Base-New Tradeoff (BNT)dilemma in prompt tuning, i.e., the better the tuned model generalizes to the base (or target) task, the worse it generalizes to…

cs.CV2023★ 3 cited

MSFlow: Multi-Scale Flow-based Framework for Unsupervised Anomaly Detection

Yixuan Zhou, Xing Xu, Jingkuan Song +2

Unsupervised anomaly detection (UAD) attracts a lot of research interest and drives widespread applications, where only anomaly-free samples are available for training. Some UAD ap…

cs.CV2023★ 1 cited

CIParsing: Unifying Causality Properties into Multiple Human Parsing

Xiaojia Chen, Xuanhan Wang, Lianli Gao +3

Existing methods of multiple human parsing (MHP) apply statistical models to acquire underlying associations between images and labeled body parts. However, acquired associations o…

cs.CV2023★ 2 cited

Informative Scene Graph Generation via Debiasing

Lianli Gao, Xinyu Lyu, Yuyu Guo +5

Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g. "on"…

cs.CV2023

MobileVidFactory: Automatic Diffusion-Based Social Media Video Generation for Mobile Devices from Text

Junchen Zhu, Huan Yang, Wenjing Wang +8

Videos for mobile devices become the most popular access to share and acquire information recently. For the convenience of users' creation, in this paper, we present a system, name…

cs.CV2023★ 1 cited

MovieFactory: Automatic Movie Creation from Text using Large Generative Models for Language and Images

Junchen Zhu, Huan Yang, Huiguo He +6

In this paper, we present MovieFactory, a powerful framework to generate cinematic-picture (30721280), film-style (multi-scene), and multi-modality (sounding) movies on the…

cs.CV2023

CageViT: Convolutional Activation Guided Efficient Vision Transformer

Hao Zheng, Jinbao Wang, Xiantong Zhen +3

Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input…

cs.CV2023★ 5 cited

Prototype-based Embedding Network for Scene Graph Generation

Chaofan Zheng, Xinyu Lyu, Lianli Gao +2

Current Scene Graph Generation (SGG) methods explore contextual information to predict relationships among entity pairs. However, due to the diverse visual appearance of numerous p…

cs.CV2023★ 3 cited

Boosting Adversarial Attacks by Leveraging Decision Boundary Information

Boheng Zeng, LianLi Gao, QiLong Zhang +3

Due to the gap between a substitute model and a victim model, the gradient-based noise generated from a substitute model may have low transferability for a victim model since their…

cs.CV2023★ 2 cited

DETA: Denoised Task Adaptation for Few-Shot Learning

Ji Zhang, Lianli Gao, Xu Luo +2

Test-time task adaptation in few-shot learning aims to adapt a pre-trained task-agnostic model for capturing taskspecific knowledge of the test task, rely only on few-labeled suppo…

cs.CV2022★ 30 cited

Hyperbolic Hierarchical Contrastive Hashing

Rukai Wei, Yu Liu, Jingkuan Song +2

Hierarchical semantic structures, naturally existing in real-world datasets, can assist in capturing the latent distribution of data to learn robust hash codes for retrieval system…

cs.CV2022

Progressive Tree-Structured Prototype Network for End-to-End Image Captioning

Pengpeng Zeng, Jinkuan Zhu, Jingkuan Song +1

Studies of image captioning are shifting towards a trend of a fully end-to-end paradigm by leveraging powerful visual pre-trained models and transformer-based generation architectu…

cs.CV2022

Learning Dual-Fused Modality-Aware Representations for RGBD Tracking

Shang Gao, Jinyu Yang, Zhe Li +3

With the development of depth sensors in recent years, RGBD object tracking has received significant attention. Compared with the traditional RGB object tracking, the addition of t…

cs.CV2022★ 2 cited

A Lower Bound of Hash Codes' Performance

Xiaosu Zhu, Jingkuan Song, Yu Lei +2

As a crucial approach for compact representation learning, hashing has achieved great success in effectiveness and efficiency. Numerous heuristic Hamming space metric learning obje…

cs.CV2022★ 15 cited

Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks

Shengming Yuan, Qilong Zhang, Lianli Gao +2

Unrestricted color attacks, which manipulate semantically meaningful color of an image, have shown their stealthiness and success in fooling both human eyes and deep neural network…