39 citations · 96 across the 23 of their papers we have counts for
23 papers
Mutual Information Guided Optimal Transport for Unsupervised Visible-Infrared Person Re-identification
Zhizhong Zhang, Jiangming Wang, Xin Tan +4
Unsupervised visible infrared person re-identification (USVI-ReID) is a challenging retrieval task that aims to retrieve cross-modality pedestrian images without using any label in…
FastLGS: Speeding up Language Embedded Gaussians with Feature Grid Mapping
Yuzhou Ji, He Zhu, Junshu Tang +4
The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding applicat…
Robust Pseudo-label Learning with Neighbor Relation for Unsupervised Visible-Infrared Person Re-Identification
Xiangbo Yin, Jiangming Shi, Yachao Zhang +4
Unsupervised Visible-Infrared Person Re-identification (USVI-ReID) presents a formidable challenge, which aims to match pedestrian images across visible and infrared modalities wit…
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection
Xiaofan Li, Zhizhong Zhang, Xin Tan +4
The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering. F…
DEMOS: Dynamic Environment Motion Synthesis in 3D Scenes via Local Spherical-BEV Perception
Jingyu Gong, Min Wang, Wentao Liu +4
Motion synthesis in real-world 3D scenes has recently attracted much attention. However, the static environment assumption made by most current methods usually cannot be satisfied…
Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification
Jiangming Shi, Xiangbo Yin, Yachao Zhang +3
Unsupervised visible-infrared person re-identification (USVI-ReID) aims to match specified people in infrared images to visible images without annotations, and vice versa. USVI-ReI…
Multi-Memory Matching for Unsupervised Visible-Infrared Person Re-Identification
Jiangming Shi, Xiangbo Yin, Yeyun Chen +4
Unsupervised visible-infrared person re-identification (USL-VI-ReID) is a promising yet challenging retrieval task. The key challenges in USL-VI-ReID are to effectively generate ps…
Beyond the Label Itself: Latent Labels Enhance Semi-supervised Point Cloud Panoptic Segmentation
Yujun Chen, Xin Tan, Zhizhong Zhang +2
As the exorbitant expense of labeling autopilot datasets and the growing trend of utilizing unlabeled data, semi-supervised segmentation on point clouds becomes increasingly impera…
COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction
Qihang Ma, Xin Tan, Yanyun Qu +3
The autonomous driving community has shown significant interest in 3D occupancy prediction, driven by its exceptional geometric perception and general object recognition capabiliti…
Multi-modal In-Context Learning Makes an Ego-evolving Scene Text Recognizer
Zhen Zhao, Jingqun Tang, Chunhui Lin +6
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is…
Cross-Stream Contrastive Learning for Self-Supervised Skeleton-Based Action Recognition
Ding Li, Yongqiang Tang, Zhizhong Zhang +1
Self-supervised skeleton-based action recognition enjoys a rapid growth along with the development of contrastive learning. The existing methods rely on imposing invariance to augm…
ShakingBot: Dynamic Manipulation for Bagging
Ningquan Gu, Zhizhong Zhang, Ruhan He +1
Bag manipulation through robots is complex and challenging due to the deformability of the bag. Based on dynamic manipulation strategy, we propose a new framework, ShakingBot, for…
High-Resolution GAN Inversion for Degraded Images in Large Diverse Datasets
Yanbo Wang, Chuming Lin, Donghao Luo +3
The last decades are marked by massive and diverse image data, which shows increasingly high resolution and quality. However, some images we obtained may be corrupted, affecting th…
Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
Tianfang Sun, Zhizhong Zhang, Xin Tan +3
Weakly supervised point cloud semantic segmentation methods that require 1\% or fewer labels, hoping to realize almost the same performance as fully supervised approaches, which re…
Attentive pooling for Group Activity Recognition
Ding Li, Yuan Xie, Wensheng Zhang +2
In group activity recognition, hierarchical framework is widely adopted to represent the relationships between individuals and their corresponding group, and has achieved promising…
Boosting Night-time Scene Parsing with Learnable Frequency
Zhifeng Xie, Sen Wang, Ke Xu +4
Night-Time Scene Parsing (NTSP) is essential to many vision applications, especially for autonomous driving. Most of the existing methods are proposed for day-time scene parsing. T…
Variational Distillation for Multi-View Learning
Xudong Tian, Zhizhong Zhang, Cong Wang +6
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions. Howev…
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
Yawei Li, Kai Zhang, Radu Timofte +108
This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-reso…
Multi-scale 2D Representation Learning for weakly-supervised moment retrieval
Ding Li, Rui Wu, Yongqiang Tang +2
Video moment retrieval aims to search the moment most relevant to a given language query. However, most existing methods in this community often require temporal boundary annotatio…
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
Yanbo Wang, Shaohui Lin, Yanyun Qu +4
Convolutional neural networks (CNNs) are highly successful for super-resolution (SR) but often require sophisticated architectures with heavy memory cost and computational overhead…
Contrastive Learning for Compact Single Image Dehazing
Haiyan Wu, Yanyun Qu, Shaohui Lin +5
Single image dehazing is a challenging ill-posed problem due to the severe information degeneration. However, existing deep learning based dehazing methods only adopt clear images…
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
Xudong Tian, Zhizhong Zhang, Shaohui Lin +3
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing…
Effective Image Retrieval via Multilinear Multi-index Fusion
Zhizhong Zhang, Yuan Xie, Wensheng Zhang +1
Multi-index fusion has demonstrated impressive performances in retrieval task by integrating different visual representations in a unified framework. However, previous works mainly…