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20232026
most citedUniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition

35 citations · 77 across the 22 of their papers we have counts for

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19 papers · 1 filter

cs.CV2026

REEL: Learning to Retrieve, Evaluate, and Evolve Visual Memory for Any Long-Horizon Multi-Shot Video Generation

Hang Xu, Guohui Zhang, Xiaoxiao Ma +7

Memory-based long-video generation aims to combine user control with long-range visual consistency. We organize this process into three functional components: a planner, an adapter…

cs.CV2026

Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning

Yijun Yang, Shenghe Zheng, Wenbo Li +8

Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the physical world. We argue th…

cs.CV2026

ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training

Xionghao Wu, Yijun Yang, Shiyang Zhou +17

Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectories are expensive to collect…

cs.CV2026

JoyAI-Video-Edit: Real-Time Open-Ended Video Editing with Autoregressive Diffusion

Yicheng Xiao, Wenxun Dai, Xinran Qin +22

Real-time video editing requires low-latency causal generation with bounded computational resources while preserving source fidelity and long-term temporal consistency. We present…

cs.CV2026

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

Yong Liu, Xiaolong Fu, Zihang Xu +10

We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for t…

cs.CV2026

AnchorEdit: Maintaining Temporal Consistency in Multi-turn Image Editing via Causal Memory

Hang Xu, Xiaoxiao Ma, Guohui Zhang +7

Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successive steps. While existing resea…

cs.CV2026

OmniNFT: Modality-wise Omni Diffusion Reinforcement for Joint Audio-Video Generation

Guohui Zhang, XiaoXiao Ma, Jie Huang +9

Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal alignment, and fine-grained synch…

cs.CV2026

Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence

Yanbing Zhang, Bo Wang, Jianhui Liu +9

Current Large Multimodal Models (LMMs) struggle with spatial reasoning tasks requiring viewpoint-dependent understanding, largely because they are confined to a single, static obse…

cs.CV2026

SpatialEdit: Benchmarking Fine-Grained Image Spatial Editing

Yicheng Xiao, Wenhu Zhang, Lin Song +10

Image spatial editing performs geometry-driven transformations, allowing precise control over object layout and camera viewpoints. Current models are insufficient for fine-grained…

cs.CV2026

LongVPO: From Anchored Cues to Self-Reasoning for Long-Form Video Preference Optimization

Zhenpeng Huang, Jiaqi Li, Zihan Jia +6

We present LongVPO, a novel two-stage Direct Preference Optimization framework that enables short-context vision-language models to robustly understand ultra-long videos without an…

cs.CV2025

HaploOmni: Unified Single Transformer for Multimodal Video Understanding and Generation

Yicheng Xiao, Lin Song, Rui Yang +6

With the advancement of language models, unified multimodal understanding and generation have made significant strides, with model architectures evolving from separated components…

cs.CV2025

DetailFusion: A Dual-branch Framework with Detail Enhancement for Composed Image Retrieval

Yuxin Yang, Yinan Zhou, Yuxin Chen +8

Composed Image Retrieval (CIR) aims to retrieve target images from a gallery based on a reference image and modification text as a combined query. Recent approaches focus on balanc…

cs.CV2025

From Prediction to Perfection: Introducing Refinement to Autoregressive Image Generation

Cheng Cheng, Lin Song, Di An +4

Autoregressive (AR) image generators offer a language-model-friendly approach to image generation by predicting discrete image tokens in a causal sequence. However, unlike diffusio…

cs.CV2024

YOLO-UniOW: Efficient Universal Open-World Object Detection

Lihao Liu, Juexiao Feng, Hui Chen +4

Traditional object detection models are constrained by the limitations of closed-set datasets, detecting only categories encountered during training. While multimodal models have e…

cs.CV2024★ 1 cited

SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Yuying Ge, Sijie Zhao, Jinguo Zhu +6

The rapid evolution of multimodal foundation model has demonstrated significant progresses in vision-language understanding and generation, e.g., our previous work SEED-LLaMA. Howe…

cs.CV2024★ 28 cited

YOLO-World: Real-Time Open-Vocabulary Object Detection

Tianheng Cheng, Lin Song, Yixiao Ge +3

The You Only Look Once (YOLO) series of detectors have established themselves as efficient and practical tools. However, their reliance on predefined and trained object categories…

cs.CV2023★ 35 cited

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition

Xiaohan Ding, Yiyuan Zhang, Yixiao Ge +4

Large-kernel convolutional neural networks (ConvNets) have recently received extensive research attention, but two unresolved and critical issues demand further investigation. 1) T…

cs.CV2023★ 10 cited

Meta-Adapter: An Online Few-shot Learner for Vision-Language Model

Cheng Cheng, Lin Song, Ruoyi Xue +4

The contrastive vision-language pre-training, known as CLIP, demonstrates remarkable potential in perceiving open-world visual concepts, enabling effective zero-shot image recognit…

cs.CV2023★ 1 cited

Sticker820K: Empowering Interactive Retrieval with Stickers

Sijie Zhao, Yixiao Ge, Zhongang Qi +4

Stickers have become a ubiquitous part of modern-day communication, conveying complex emotions through visual imagery. To facilitate the development of more powerful algorithms for…