1 citations · 1 across the 12 of their papers we have counts for
13 papers
PAGER: Bridging the Semantic-Execution Gap in Point-Precise Geometric GUI Control
Jingxuan Wei, Xi Bai, Shan Liu +8
Large vision-language models have significantly advanced GUI agents, enabling executable interaction across web, mobile, and desktop interfaces. Yet these gains largely rely on a f…
PanoWorld: Geometry-Consistent Panoramic Video World Modeling
Le Jiang, Xiangyu Bai, Bishoy Galoaa +7
We present PanoWorld, a panoramic video world model that generates geometry-consistent 360 video from a single image and a caption. Existing panoramic video methods optimi…
HORNet: Task-Guided Frame Selection for Video Question Answering with Vision-Language Models
Xiangyu Bai, Bishoy Galoaa, Sarah Ostadabbas
Video question answering (VQA) with vision-language models (VLMs) depends critically on which frames are selected from the input video, yet most systems rely on uniform or heuristi…
Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding
Xianjin Wu, Dingkang Liang, Tianrui Feng +5
While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-grained geometric reasoning and…
Motion-o: Trajectory-Grounded Video Reasoning
Bishoy Galoaa, Shayda Moezzi, Xiangyu Bai +1
Recent video reasoning models increasingly produce spatio-temporal evidence chains that localize objects at specific timestamps. While these traces improve interpretability by grou…
UniTrack: Differentiable Graph Representation Learning for Multi-Object Tracking
Bishoy Galoaa, Xiangyu Bai, Utsav Nandi +3
We present UniTrack, a plug-and-play graph-theoretic loss function designed to significantly enhance multi-object tracking (MOT) performance by directly optimizing tracking-specifi…
Structure Over Scale: Learning Visual Reasoning from Pedagogical Video
Bishoy Galoaa, Xiangyu Bai, Sarah Ostadabbas
State-of-the-art vision-language models (VLMs) score impressively on video benchmarks yet stumble on basic visual reasoning tasks involving spatial relations, navigation, and objec…
Lang2Motion: Bridging Language and Motion through Joint Embedding Spaces
Bishoy Galoaa, Xiangyu Bai, Sarah Ostadabbas
We present Lang2Motion, a framework for language-guided point trajectory generation by aligning motion manifolds with joint embedding spaces. Unlike prior work focusing on human mo…
MoReGen: Multi-Agent Motion-Reasoning Engine for Code-based Text-to-Video Synthesis
Xiangyu Bai, He Liang, Bishoy Galoaa +4
While text-to-video (T2V) generation has achieved remarkable progress in photorealism, generating intent-aligned videos that faithfully obey physics principles remains a core chall…
Look Around and Pay Attention: Multi-camera Point Tracking Reimagined with Transformers
Bishoy Galoaa, Xiangyu Bai, Shayda Moezzi +4
This paper presents LAPA (Look Around and Pay Attention), a novel end-to-end transformer-based architecture for multi-camera point tracking that integrates appearance-based matchin…
Learning Multimodal AI Algorithms for Amplifying Limited User Input into High-dimensional Control Space
Ali Rabiee, Sima Ghafoori, MH Farhadi +5
Current invasive assistive technologies are designed to infer high-dimensional motor control signals from severely paralyzed patients. However, they face significant challenges, in…
STREAMS: An Assistive Multimodal AI Framework for Empowering Biosignal Based Robotic Controls
Ali Rabiee, Sima Ghafoori, Xiangyu Bai +2
End-effector based assistive robots face persistent challenges in generating smooth and robust trajectories when controlled by human's noisy and unreliable biosignals such as muscl…
Bridging the Domain Gap between Synthetic and Real-World Data for Autonomous Driving
Xiangyu Bai, Yedi Luo, Le Jiang +4
Modern autonomous systems require extensive testing to ensure reliability and build trust in ground vehicles. However, testing these systems in the real-world is challenging due to…