2 citations · 3 across the 19 of their papers we have counts for
16 papers · 1 filter
MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models
Sihan Chen, Jiale Li, Jianghang Lin +1
Video Large Language Models (VideoLLMs) have shown strong progress in video understanding, yet they still suffer from hallucinations that are inconsistent with visual evidence. Exi…
Active-SAOOD: Active Sparsely Annotated Oriented Object Detection in Remote Sensing Images
Yu Lin, Jianghang Lin, Kai Ye +2
Reducing the annotation cost of oriented object detection in remote sensing remains a major challenge. Recently, sparse annotation has gained attention for effectively reducing ann…
HieraVid: Hierarchical Token Pruning for Fast Video Large Language Models
Yansong Guo, Chaoyang Zhu, Jiayi Ji +2
Video Large Language Models (VideoLLMs) have demonstrated impressive capabilities in video understanding, yet the massive number of input video tokens incurs a significant computat…
Referring Industrial Anomaly Segmentation
Pengfei Yue, Xiaokang Jiang, Yilin Lu +3
Industrial Anomaly Detection (IAD) is vital for manufacturing, yet traditional methods face significant challenges: unsupervised approaches yield rough localizations requiring manu…
Evolving, Not Training: Zero-Shot Reasoning Segmentation via Evolutionary Prompting
Kai Ye, Xiaotong You, Jianghang Lin +3
Reasoning Segmentation requires models to interpret complex, context-dependent linguistic queries to achieve pixel-level localization. Current dominant approaches rely heavily on S…
Generate Aligned Anomaly: Region-Guided Few-Shot Anomaly Image-Mask Pair Synthesis for Industrial Inspection
Yilin Lu, Jianghang Lin, Linhuang Xie +5
Anomaly inspection plays a vital role in industrial manufacturing, but the scarcity of anomaly samples significantly limits the effectiveness of existing methods in tasks such as l…
What You Perceive Is What You Conceive: A Cognition-Inspired Framework for Open Vocabulary Image Segmentation
Jianghang Lin, Yue Hu, Jiangtao Shen +4
Open vocabulary image segmentation tackles the challenge of recognizing dynamically adjustable, predefined novel categories at inference time by leveraging vision-language alignmen…
Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation
Jianghang Lin, Yilin Lu, Yunhang Shen +4
Semi-Supervised Instance Segmentation (SSIS) involves classifying and grouping image pixels into distinct object instances using limited labeled data. This learning paradigm usuall…
STeacher: Step-by-step Teacher for Sparsely Annotated Oriented Object Detection
Yu Lin, Jianghang Lin, Kai Ye +5
Although fully-supervised oriented object detection has made significant progress in multimodal remote sensing image understanding, it comes at the cost of labor-intensive annotati…
AnomalyPainter: Vision-Language-Diffusion Synergy for Zero-Shot Realistic and Diverse Industrial Anomaly Synthesis
Zhangyu Lai, Yilin Lu, Xinyang Li +5
While existing anomaly synthesis methods have made remarkable progress, achieving both realism and diversity in synthesis remains a major obstacle. To address this, we propose Anom…
Exploring Semantic Consistency and Style Diversity for Domain Generalized Semantic Segmentation
Hongwei Niu, Linhuang Xie, Jianghang Lin +1
Domain Generalized Semantic Segmentation (DGSS) seeks to utilize source domain data exclusively to enhance the generalization of semantic segmentation across unknown target domains…
EOV-Seg: Efficient Open-Vocabulary Panoptic Segmentation
Hongwei Niu, Jie Hu, Jianghang Lin +2
Open-vocabulary panoptic segmentation aims to segment and classify everything in diverse scenes across an unbounded vocabulary. Existing methods typically employ two-stage or singl…
HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection
Liujuan Cao, Jianghang Lin, Zebo Hong +4
Most WSOD methods rely on traditional object proposals to generate candidate regions and are confronted with unstable training, which easily gets stuck in a poor local optimum. In…
Depth-Guided Semi-Supervised Instance Segmentation
Xin Chen, Jie Hu, Xiawu Zheng +3
Semi-Supervised Instance Segmentation (SSIS) aims to leverage an amount of unlabeled data during training. Previous frameworks primarily utilized the RGB information of unlabeled i…
GOI: Find 3D Gaussians of Interest with an Optimizable Open-vocabulary Semantic-space Hyperplane
Yansong Qu, Shaohui Dai, Xinyang Li +4
3D open-vocabulary scene understanding, crucial for advancing augmented reality and robotic applications, involves interpreting and locating specific regions within a 3D space as d…
Weakly Supervised Open-Vocabulary Object Detection
Jianghang Lin, Yunhang Shen, Bingquan Wang +3
Despite weakly supervised object detection (WSOD) being a promising step toward evading strong instance-level annotations, its capability is confined to closed-set categories withi…