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20242026
most citedCVP: Central-Peripheral Vision-Inspired Multimodal Model for Spatial Reasoning

1 citations · 2 across the 12 of their papers we have counts for

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15 papers · 1 filter

cs.CV2026

LIFT: Layout-In-Future Video Generation under Large Viewpoint Change via On-Policy Self-Distillation

Shengxiang Ji, Boyang Wang, Haiyang Xu +9

We introduce LIFT, a unified image-to-video generation framework that complements camera control with Layout-In-FuTure control, enabling users to specify what should appear in a fu…

cs.CV2026

RECAP-Forcing: Retaining Content Appearances for Long Video Generation

Haiyang Xu, Zheng Ding, Zhuowen Tu

Long autoregressive video generation faces a fundamental memory challenge: with a finite attention window, a model must decide which information from an ever-expanding history to r…

cs.CV2026

Hyper^2: Unleashing Hyperbolic Geometry's Full Potential via Dual-Space Consistency

Guantian Zheng, Haiyang Xu, Tianyu Gao

HyperbolicCD pioneered hyperbolic geometry for point cloud completion by replacing the Euclidean Chamfer distance with arcosh(1+alpha||x-y||^2), but the reported gains are modest (…

cs.CV2026

SemLayer: Semantic-aware Generative Segmentation and Layer Construction for Abstract Icons

Haiyang Xu, Ronghuan Wu, Li-Yi Wei +5

Graphic icons are a cornerstone of modern design workflows, yet they are often distributed as flattened single-path or compound-path graphics, where the original semantic layering…

cs.CV2026

CyCLeGen: Cycle-Consistent Layout Prediction and Image Generation in Vision Foundation Models

Xiaojun Shan, Haoyu Shen, Yucheng Mao +5

We present CyCLeGen, a unified vision-language foundation model capable of both image understanding and image generation within a single autoregressive framework. Unlike existing v…

cs.CV2025★ 1 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 (…

cs.CV2025

DepR: Depth Guided Single-view Scene Reconstruction with Instance-level Diffusion

Qingcheng Zhao, Xiang Zhang, Haiyang Xu +4

We propose DepR, a depth-guided single-view scene reconstruction framework that integrates instance-level diffusion within a compositional paradigm. Instead of reconstructing the e…

cs.CV2025★ 1 cited

Science-T2I: Addressing Scientific Illusions in Image Synthesis

Jialuo Li, Wenhao Chai, Xingyu Fu +2

Current image generation models produce visually compelling but scientifically implausible images, exposing a fundamental gap between visual fidelity and physical realism. In this…

cs.CV2024

OmniControlNet: Dual-stage Integration for Conditional Image Generation

Yilin Wang, Haiyang Xu, Xiang Zhang +4

We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating i…

cs.CV2024

Bayesian Diffusion Models for 3D Shape Reconstruction

Haiyang Xu, Yu Lei, Zeyuan Chen +4

We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-u…