activity
20242026
most citedSAPNet++: Evolving Point-Prompted Instance Segmentation with Semantic and Spatial Awareness

1 citations · 1 across the 8 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

Zhaoyang Wei, Bowen Jiang, Xumeng Han +6

While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates significantly in complex scenes unde…

cs.CV2026

GeoBridge: Decoupled Semantic Conditioning for Generative Image Geolocalization

Zhiyang Dou, Xumeng Han, Fengde Peng +4

Multimodal large language models (MLLMs) have advanced image geolocalization mainly by improving how they reason about geographic cues. How that reasoning isdecoded into coordinate…

cs.CV2026

HeroGS: Hierarchical Guidance for Robust 3D Gaussian Splatting under Sparse Views

Jiashu Li, Xumeng Han, Zhaoyang Wei +5

3D Gaussian Splatting (3DGS) has recently emerged as a promising approach in novel view synthesis, combining photorealistic rendering with real-time efficiency. However, its succes…

cs.CV2026★ 1 cited

SAPNet++: Evolving Point-Prompted Instance Segmentation with Semantic and Spatial Awareness

Zhaoyang Wei, Xumeng Han, Xuehui Yu +4

Single-point annotation is increasingly prominent in visual tasks for labeling cost reduction. However, it challenges tasks requiring high precision, such as the point-prompted ins…

cs.CV2025

Evidence-Grounded Trustworthy Multimodal Reasoning and Evaluation Benchmark in Complex Urban Scenes

Zhaoyang Wei, Bowen Jiang, Xumeng Han +6

While Multimodal Large Language Models (MLLMs) demonstrate impressive performance in benign scenarios, their cognitive reliability deteriorates significantly in complex scenes unde…

cs.CV2025

P2Object: Single Point Supervised Object Detection and Instance Segmentation

Pengfei Chen, Xuehui Yu, Xumeng Han +5

Object recognition using single-point supervision has attracted increasing attention recently. However, the performance gap compared with fully-supervised algorithms remains large.…

cs.CV2025

Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection

Yi Yu, Xue Yang, Yansheng Li +3

Accurately estimating the orientation of visual objects with compact rotated bounding boxes (RBoxes) has become a prominent demand, which challenges existing object detection parad…

cs.CV2024

Towards Interactive Global Geolocation Assistant

Zhiyang Dou, Zipeng Wang, Xumeng Han +3

Global geolocation, which seeks to predict the geographical location of images captured anywhere in the world, is one of the most challenging tasks in the field of computer vision.…

cs.CV2024

ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts

Xumeng Han, Longhui Wei, Zhiyang Dou +6

Mixture-of-Experts (MoE) models embody the divide-and-conquer concept and are a promising approach for increasing model capacity, demonstrating excellent scalability across multipl…

cs.CV2024

SAM-CP: Marrying SAM with Composable Prompts for Versatile Segmentation

Pengfei Chen, Lingxi Xie, Xinyue Huo +5

The Segment Anything model (SAM) has shown a generalized ability to group image pixels into patches, but applying it to semantic-aware segmentation still faces major challenges. Th…