35 citations · 77 across the 22 of their papers we have counts for
25 papers
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…
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…
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…
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…
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…
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…
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation
Lin Song, Wenbo Li, Guoqing Ma +16
We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text-to-image generation, and instruction-guided image editing. JoyAI-Image couples a spatia…
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…
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…
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…
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…
LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
Yicheng Xiao, Lin Song, Rui Yang +4
Recent advances have highlighted the benefits of scaling language models to enhance performance across a wide range of NLP tasks. However, these approaches still face limitations i…
MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO
Yicheng Xiao, Lin Song, Yukang Chen +7
Recent text-to-image systems face limitations in handling multimodal inputs and complex reasoning tasks. We introduce MindOmni, a unified multimodal large language model that addre…
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…
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…
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…
HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding
Rui Yang, Lin Song, Yicheng Xiao +4
Recent advancements in large language models (LLMs) have significantly propelled the development of large multi-modal models (LMMs), highlighting the potential for general and inte…
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…
GrootVL: Tree Topology is All You Need in State Space Model
Yicheng Xiao, Lin Song, Shaoli Huang +5
The state space models, employing recursively propagated features, demonstrate strong representation capabilities comparable to Transformer models and superior efficiency. However,…
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…
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…
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…
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…
InstructDET: Diversifying Referring Object Detection with Generalized Instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang +8
We propose InstructDET, a data-centric method for referring object detection (ROD) that localizes target objects based on user instructions. While deriving from referring expressio…