217 citations · 548 across the 29 of their papers we have counts for
33 papers
ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing
Wei Sun, Weixia Zhang, Linhan Cao +30
This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for Hi…
Image Segmentation in Foundation Model Era: A Survey
Tianfei Zhou, Wang Xia, Fei Zhang +5
Image segmentation is a long-standing challenge in computer vision, studied continuously over several decades, as evidenced by seminal algorithms such as N-Cut, FCN, and MaskFormer…
Nonverbal Interaction Detection
Jianan Wei, Tianfei Zhou, Yi Yang +1
This work addresses a new challenge of understanding human nonverbal interaction in social contexts. Nonverbal signals pervade virtually every communicative act. Our gestures, faci…
CORE: Cooperative Reconstruction for Multi-Agent Perception
Binglu Wang, Lei Zhang, Zhaozhong Wang +2
This paper presents CORE, a conceptually simple, effective and communication-efficient model for multi-agent cooperative perception. It addresses the task from a novel perspective…
CLUSTSEG: Clustering for Universal Segmentation
James Liang, Tianfei Zhou, Dongfang Liu +1
We present CLUSTSEG, a general, transformer-based framework that tackles different image segmentation tasks (i.e., superpixel, semantic, instance, and panoptic) through a unified n…
Learning Anchor Transformations for 3D Garment Animation
Fang Zhao, Zekun Li, Shaoli Huang +5
This paper proposes an anchor-based deformation model, namely AnchorDEF, to predict 3D garment animation from a body motion sequence. It deforms a garment mesh template by a mixtur…
Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation
Liulei Li, Wenguan Wang, Tianfei Zhou +2
The objective of this paper is self-supervised learning of video object segmentation. We develop a unified framework which simultaneously models cross-frame dense correspondence fo…
FedFA: Federated Feature Augmentation
Tianfei Zhou, Ender Konukoglu
Federated learning is a distributed paradigm that allows multiple parties to collaboratively train deep models without exchanging the raw data. However, the data distribution among…
Unsupervised Superpixel Generation using Edge-Sparse Embedding
Jakob Geusen, Gustav Bredell, Tianfei Zhou +1
Partitioning an image into superpixels based on the similarity of pixels with respect to features such as colour or spatial location can significantly reduce data complexity and im…
Visual Recognition with Deep Nearest Centroids
Wenguan Wang, Cheng Han, Tianfei Zhou +1
We devise deep nearest centroids (DNC), a conceptually elegant yet surprisingly effective network for large-scale visual recognition, by revisiting Nearest Centroids, one of the mo…
Rethinking Semantic Segmentation: A Prototype View
Tianfei Zhou, Wenguan Wang, Ender Konukoglu +1
Prevalent semantic segmentation solutions, despite their different network designs (FCN based or attention based) and mask decoding strategies (parametric softmax based or pixel-qu…
Deep Hierarchical Semantic Segmentation
Liulei Li, Tianfei Zhou, Wenguan Wang +2
Humans are able to recognize structured relations in observation, allowing us to decompose complex scenes into simpler parts and abstract the visual world in multiple levels. Howev…
Locality-Aware Inter-and Intra-Video Reconstruction for Self-Supervised Correspondence Learning
Liulei Li, Tianfei Zhou, Wenguan Wang +3
Our target is to learn visual correspondence from unlabeled videos. We develop LIIR, a locality-aware inter-and intra-video reconstruction framework that fills in three missing pie…
Visual Abductive Reasoning
Chen Liang, Wenguan Wang, Tianfei Zhou +1
Abductive reasoning seeks the likeliest possible explanation for partial observations. Although abduction is frequently employed in human daily reasoning, it is rarely explored in…
Regional Semantic Contrast and Aggregation for Weakly Supervised Semantic Segmentation
Tianfei Zhou, Meijie Zhang, Fang Zhao +1
Learning semantic segmentation from weakly-labeled (e.g., image tags only) data is challenging since it is hard to infer dense object regions from sparse semantic tags. Despite bei…
Local-Global Context Aware Transformer for Language-Guided Video Segmentation
Chen Liang, Wenguan Wang, Tianfei Zhou +3
We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and…
Detail-Preserving Transformer for Light Field Image Super-Resolution
Shunzhou Wang, Tianfei Zhou, Yao Lu +1
Recently, numerous algorithms have been developed to tackle the problem of light field super-resolution (LFSR), i.e., super-resolving low-resolution light fields to gain high-resol…
Deep multi-modal aggregation network for MR image reconstruction with auxiliary modality
Chun-Mei Feng, Huazhu Fu, Tianfei Zhou +3
Magnetic resonance (MR) imaging produces detailed images of organs and tissues with better contrast, but it suffers from a long acquisition time, which makes the image quality vuln…
Quality-Aware Memory Network for Interactive Volumetric Image Segmentation
Tianfei Zhou, Liulei Li, Gustav Bredell +2
Despite recent progress of automatic medical image segmentation techniques, fully automatic results usually fail to meet the clinical use and typically require further refinement.…
A Survey on Deep Learning Technique for Video Segmentation
Tianfei Zhou, Fatih Porikli, David Crandall +2
Video segmentation -- partitioning video frames into multiple segments or objects -- plays a critical role in a broad range of practical applications, from enhancing visual effects…
Rethinking Cross-modal Interaction from a Top-down Perspective for Referring Video Object Segmentation
Chen Liang, Yu Wu, Tianfei Zhou +4
Referring video object segmentation (RVOS) aims to segment video objects with the guidance of natural language reference. Previous methods typically tackle RVOS through directly gr…
Target-Aware Object Discovery and Association for Unsupervised Video Multi-Object Segmentation
Tianfei Zhou, Jianwu Li, Xueyi Li +1
This paper addresses the task of unsupervised video multi-object segmentation. Current approaches follow a two-stage paradigm: 1) detect object proposals using pre-trained Mask R-C…
Face Forensics in the Wild
Tianfei Zhou, Wenguan Wang, Zhiyuan Liang +1
On existing public benchmarks, face forgery detection techniques have achieved great success. However, when used in multi-person videos, which often contain many people active in t…
Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsing
Tianfei Zhou, Wenguan Wang, Si Liu +2
To address the challenging task of instance-aware human part parsing, a new bottom-up regime is proposed to learn category-level human semantic segmentation as well as multi-person…