activity
20232026
most citedLearning Motion and Temporal Cues for Unsupervised Video Object Segmentation

12 citations · 19 across the 13 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2026

Vinci2: Providing Proactive Assistance in Continuous Egocentric Videos

Gong Sitong, Tianyu Yan, Caixin Kang +6

When should an intelligent assistant speak up without being asked? Continuous egocentric video offers rich, evolving context that enables a new form of assistance: one that is proa…

cs.CV2026

Towards Cross-Platform Generalization: Domain Adaptive 3D Detection with Augmentation and Pseudo-Labeling

Xiyan Feng, Wenbo Zhang, Lu Zhang +3

This technical report represents the award-winning solution to the Cross-platform 3D Object Detection task in the RoboSense2025 Challenge. Our approach is built upon PVRCNN++, an e…

cs.CV2025

Parameter Aware Mamba Model for Multi-task Dense Prediction

Xinzhuo Yu, Yunzhi Zhuge, Sitong Gong +3

Understanding the inter-relations and interactions between tasks is crucial for multi-task dense prediction. Existing methods predominantly utilize convolutional layers and attenti…

cs.CV2025

FineRS: Fine-grained Reasoning and Segmentation of Small Objects with Reinforcement Learning

Lu Zhang, Jiazuo Yu, Haomiao Xiong +4

Multi-modal Large Language Models (MLLMs) have shown remarkable capabilities across a wide range of vision-language tasks. However, due to the restricted input resolutions, MLLMs f…

cs.CV2025★ 12 cited

Learning Motion and Temporal Cues for Unsupervised Video Object Segmentation

Yunzhi Zhuge, Hongyu Gu, Lu Zhang +2

In this paper, we address the challenges in unsupervised video object segmentation (UVOS) by proposing an efficient algorithm, termed MTNet, which concurrently exploits motion and…

cs.CV2024★ 5 cited

MoTrans: Customized Motion Transfer with Text-driven Video Diffusion Models

Xiaomin Li, Xu Jia, Qinghe Wang +5

Existing pretrained text-to-video (T2V) models have demonstrated impressive abilities in generating realistic videos with basic motion or camera movement. However, these models exh…

cs.CV2024

Deep Boosting Learning: A Brand-new Cooperative Approach for Image-Text Matching

Haiwen Diao, Ying Zhang, Shang Gao +2

Image-text matching remains a challenging task due to heterogeneous semantic diversity across modalities and insufficient distance separability within triplets. Different from prev…

cs.CV2023

Tracking with Human-Intent Reasoning

Jiawen Zhu, Zhi-Qi Cheng, Jun-Yan He +5

Advances in perception modeling have significantly improved the performance of object tracking. However, the current methods for specifying the target object in the initial frame a…

cs.CV2023

DCPT: Darkness Clue-Prompted Tracking in Nighttime UAVs

Jiawen Zhu, Huayi Tang, Zhi-Qi Cheng +5

Existing nighttime unmanned aerial vehicle (UAV) trackers follow an "Enhance-then-Track" architecture - first using a light enhancer to brighten the nighttime video, then employing…