activity
20202025
most citedNTIRE 2020 Challenge on Image Demoireing: Methods and Results

3 citations · 10 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2025

Novel Category Discovery with X-Agent Attention for Open-Vocabulary Semantic Segmentation

Jiahao Li, Yang Lu, Yachao Zhang +3

Open-vocabulary semantic segmentation (OVSS) conducts pixel-level classification via text-driven alignment, where the domain discrepancy between base category training and open-voc…

cs.CV2025

SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding

Jiawen Lin, Shiran Bian, Yihang Zhu +4

3D Visual Grounding (3DVG) aims to localize objects in 3D scenes using natural language descriptions. Although supervised methods achieve higher accuracy in constrained settings, z…

cs.LG2024

Large Continual Instruction Assistant

Jingyang Qiao, Zhizhong Zhang, Xin Tan +3

Continual Instruction Tuning (CIT) is adopted to continually instruct Large Models to follow human intent data by data. It is observed that existing gradient update would heavily d…

cs.CV2024★ 1 cited

Data-free Distillation with Degradation-prompt Diffusion for Multi-weather Image Restoration

Pei Wang, Xiaotong Luo, Yuan Xie +1

Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devi…

cs.CV2024

Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining

Tianfang Sun, Zhizhong Zhang, Xin Tan +2

LiDAR-camera 3D representation pretraining has shown significant promise for 3D perception tasks and related applications. However, two issues widely exist in this framework: 1) So…

cs.CV2024

Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception

Haoming Chen, Zhizhong Zhang, Yanyun Qu +3

An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However, establishing such an ideal framework t…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024

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…

cs.CV2023★ 3 cited

CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data

Jiangming Shi, Shanshan Zheng, Xiangbo Yin +3

Federated learning (FL) provides a decentralized machine learning paradigm where a server collaborates with a group of clients to learn a global model without accessing the clients…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 1 cited

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…

cs.CV2020

NTIRE 2020 Challenge on NonHomogeneous Dehazing

Codruta O. Ancuti, Cosmin Ancuti, Florin-Alexandru Vasluianu +49

This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results e…

cs.CV2020★ 3 cited

NTIRE 2020 Challenge on Image Demoireing: Methods and Results

Shanxin Yuan, Radu Timofte, Ales Leonardis +43

This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demo…