1 citations · 1 across the 31 of their papers we have counts for
31 papers
Kairos: A Dataset for Fine-Grained Video-Language Modeling over Space, Time, and Dynamics
Ruibo Ming, Lei Sun, Deheng Zhang +8
Many emerging video language modeling tasks require systems to move beyond clip-level abstraction and model visual content as it unfolds over extended time horizons. However, most…
Geometry-Aware Test-Time Learning for Quantitative Spatial Reasoning
Gege Zhang, Shuaicheng Niu, Gang Dai +2
Quantitative spatial reasoning in visual-language models (VLMs) aims to infer spatial distances and directional relationships among objects in 3D space from a 2D image and a natura…
GAINS: Leveraging Inconsistent Human Intervention Signals in Reinforcement Learning
Xinyi Zhang, Yinuo Zhao, Pei Ren +7
Correcting robot manipulation policies through human intervention holds great promise for real-world deployment, yet human operators are inherently imperfect in both the actions th…
Evaluation-Verification Reward for Consistent Multi-Reference Image Editing
Yingmao Miao, Pengfei Zhang, Xiaochen Lv +5
While recent image editing models have made rapid progress, multi-reference editing remains challenging, particularly in maintaining visual consistency across references and ensuri…
Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment
Geng Li, Haiwen Li, Rui Chen +3
Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks. Its progress is hindered n…
M2Note: Continual Evolution of Vision Language Models via Mistake Notebook Learning
Haiwen Li, Jing Tang, Rui Chen +2
Vision Language Models (VLMs) have demonstrated remarkable capabilities in multimodal reasoning tasks, yet they still suffer from recurring failures, such as skipping key visual ch…
DreamX-World 1.0: A General-Purpose Interactive World Model
DreamX Team, Yancheng Bai, Rui Chen +20
DreamX-World 1.0 is a general-purpose interactive text/image-to-video world model for controllable long-horizon generation. It supports camera navigation, revisits to previously ob…
Elucidating the SNR-t Bias of Diffusion Probabilistic Models
Meng Yu, Lei Sun, Jianhao Zeng +2
Diffusion Probabilistic Models have demonstrated remarkable performance across a wide range of generative tasks. However, we have observed that these models often suffer from a Sig…
From Scale to Speed: Adaptive Test-Time Scaling for Image Editing
Xiangyan Qu, Zhenlong Yuan, Jing Tang +9
Image Chain-of-Thought (Image-CoT) is a test-time scaling paradigm that improves image generation by extending inference time. Most Image-CoT methods focus on text-to-image (T2I) g…
Omni-WorldBench: Towards a Comprehensive Interaction-Centric Evaluation for World Models
Meiqi Wu, Zhixin Cai, Fufangchen Zhao +13
Video--based world models have emerged along two dominant paradigms: video generation and 3D reconstruction. However, existing evaluation benchmarks either focus narrowly on visual…
Video-CoE: Reinforcing Video Event Prediction via Chain of Events
Qile Su, Jing Tang, Rui Chen +2
Despite advances in the application of MLLMs for various video tasks, video event prediction (VEP) remains relatively underexplored. VEP requires the model to perform fine-grained…
Interp3R: Continuous-time 3D Geometry Estimation with Frames and Events
Shuang Guo, Filbert Febryanto, Lei Sun +2
In recent years, 3D visual foundation models, pioneered by pointmap-based approaches such as DUSt3R, have attracted a lot of interest, achieving impressive accuracy and strong gene…
Layer-wise Instance Binding for Regional and Occlusion Control in Text-to-Image Diffusion Transformers
Ruidong Chen, Yancheng Bai, Xuanpu Zhang +6
Region-instructed layout control in text-to-image generation is highly practical, yet existing methods suffer from limitations: (i) training-based approaches inherit data bias and…
MultiHaystack: Benchmarking Multimodal Retrieval and Reasoning over 40K Images, Videos, and Documents
Dannong Xu, Zhongyu Yang, Jun Chen +6
Multimodal large language models (MLLMs) achieve strong performance on benchmarks that evaluate text, image, or video understanding separately. However, these settings do not asses…
Edit in 2D, Verify in 3D: Reinforcement Learning for Multi-view Consistent Scene Editing
Jiyuan Wang, Chunyu Lin, Lei Sun +8
Leveraging the priors of 2D diffusion models for 3D editing has emerged as a promising paradigm. However, multi-view consistency remains challenging in edited results, and the extr…
What if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation
Zhenlong Yuan, Yue Wang, Dapeng Zhang +9
Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Open-Vocabulary Human-Object Intera…
TEXTS-Diff: TEXTS-Aware Diffusion Model for Real-World Text Image Super-Resolution
Haodong He, Xin Zhan, Yancheng Bai +3
Real-world text image super-resolution aims to restore overall visual quality and text legibility in images suffering from diverse degradations and text distortions. However, the s…
Real-world Reinforcement Learning from Suboptimal Interventions
Yinuo Zhao, Huiqian Jin, Lechun Jiang +9
Real-world reinforcement learning (RL) offers a promising approach to training precise and dexterous robotic manipulation policies in an online manner, enabling robots to learn fro…
Eevee: Towards Close-up High-resolution Video-based Virtual Try-on
Jianhao Zeng, Yancheng Bai, Ruidong Chen +7
Video virtual try-on technology provides a cost-effective solution for creating marketing videos in fashion e-commerce. However, its practical adoption is hindered by two critical…
Semantic Context Matters: Improving Conditioning for Autoregressive Models
Dongyang Jin, Ryan Xu, Jianhao Zeng +4
Recently, autoregressive (AR) models have shown strong potential in image generation, offering better scalability and easier integration with unified multi-modal systems compared t…
Video-STAR: Reinforcing Open-Vocabulary Action Recognition with Tools
Zhenlong Yuan, Xiangyan Qu, Chengxuan Qian +8
Multimodal large language models (MLLMs) have demonstrated remarkable potential in bridging visual and textual reasoning, yet their reliance on text-centric priors often limits the…
From Editor to Dense Geometry Estimator
JiYuan Wang, Chunyu Lin, Lei Sun +5
Leveraging visual priors from pre-trained text-to-image (T2I) generative models has shown success in dense prediction. However, dense prediction is inherently an image-to-image tas…
AutoDrive-R: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving
Zhenlong Yuan, Chengxuan Qian, Jing Tang +7
Vision-Language-Action (VLA) models in autonomous driving systems have recently demonstrated transformative potential by integrating multimodal perception with decision-making capa…
RAGSR: Regional Attention Guided Diffusion for Image Super-Resolution
Haodong He, Yancheng Bai, Rui Lan +4
The rich textual information of large vision-language models (VLMs) combined with the powerful generative prior of pre-trained text-to-image (T2I) diffusion models has achieved imp…