24 citations · 36 across the 14 of their papers we have counts for
12 papers · 1 filter
The Right Future for Action: Learning Action-Relevant Predictive States in World Action Models
Qiwen Gu, Jifan Li, Bingjie Gao +4
Generation-free world action models (WAMs) retain future-video prediction during training but act from internal video features at inference, leaving unclear what these features sho…
R2M-Bench: Evaluating Revisit Memory via Relative Consistency in Interactive Video World Models
Qiwen Gu, Bingjie Gao, Rui Chen +7
High similarity between first-visit and return frames does not necessarily show that a video world model remembered the scene; the intervening rollout may simply have changed very…
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
DreamX Team, Rui Chen, Xiangxiang Chu +7
We present \textbf{DreamX-Phi 1.0}, an action-conditioned video world model for robotic manipulation that, given an observed frame, a language instruction, and a prescribed action…
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…
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…
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…
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…
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…
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…
FingER: Content Aware Fine-grained Evaluation with Reasoning for AI-Generated Videos
Rui Chen, Lei Sun, Jing Tang +2
Recent advances in video generation have posed great challenges in the assessment of AI-generated content, particularly with the emergence of increasingly sophisticated models. The…
Cross-View Tracking for Multi-Human 3D Pose Estimation at over 100 FPS
Long Chen, Haizhou Ai, Rui Chen +2
Estimating 3D poses of multiple humans in real-time is a classic but still challenging task in computer vision. Its major difficulty lies in the ambiguity in cross-view association…
Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation
Rui Chen, Haizhou Ai, Chong Shang +2
It remains very challenging to build a pedestrian detection system for real world applications, which demand for both accuracy and speed. This work presents a novel hierarchical kn…