most citedCVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV20251 cited

CVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning

Zeyuan Chen, Xiang Zhang, Haiyang Xu +2

We present a central-peripheral vision-inspired framework (CVP), a simple yet effective multimodal model for spatial reasoning that draws inspiration from the two types of human vi…

cs.CV2025

MonkeyOCR v1.5 Technical Report: Unlocking Robust Document Parsing for Complex Patterns

Jiarui Zhang, Yuliang Liu, Zijun Wu +17

Document parsing is a core task in document intelligence, supporting applications such as information extraction, retrieval-augmented generation, and automated document analysis. H…

cs.CV2025

VideoNSA: Native Sparse Attention Scales Video Understanding

Enxin Song, Wenhao Chai, Shusheng Yang +5

Video understanding in multimodal language models remains limited by context length: models often miss key transition frames and struggle to maintain coherence across long time sca…

cs.CV2025

OverLayBench: A Benchmark for Layout-to-Image Generation with Dense Overlaps

Bingnan Li, Chen-Yu Wang, Haiyang Xu +7

Despite steady progress in layout-to-image generation, current methods still struggle with layouts containing significant overlap between bounding boxes. We identify two primary ch…

cs.CV2025

Exploring the Equivalence of Closed-Set Generative and Real Data Augmentation in Image Classification

Haowen Wang, Guowei Zhang, Xiang Zhang +4

In this paper, we address a key scientific problem in machine learning: Given a training set for an image classification task, can we train a generative model on this dataset to en…

cs.CV2025

YOLO-Count: Differentiable Object Counting for Text-to-Image Generation

Guanning Zeng, Xiang Zhang, Zirui Wang +4

We propose YOLO-Count, a differentiable open-vocabulary object counting model that tackles both general counting challenges and enables precise quantity control for text-to-image (…