66 citations · 216 across the 50 of their papers we have counts for
56 papers
When does fusing hand-crafted knowledge with learned representations pay? A cost-normalized benchmark of stacking, substitution, and interference
Ahmad AlMughrabi, Albert Clop, Benjamin Busam +2
Fusing prior knowledge with data-driven learning is attractive where data is scarce, yet no controlled account says when it helps, is redundant, or harms. We benchmark one fixed ha…
Pose Anything Anywhere:Model-free Object Poses from Arbitrary References
Hongli Xu, Jiaqi Hu, Junwen Huang +5
Estimating the 6D pose of unseen objects is a fundamental yet challenging problem for open-world robotics and embodied perception. Model-based methods are accurate but depend on CA…
BenchSeg: A Large-Scale Dataset and Benchmark for Multi-View Food Video Segmentation
Ahmad AlMughrabi, Guillermo Rivo, Carlos Jiménez-Farfán +6
Food image segmentation is a critical task for dietary analysis, enabling accurate estimation of food volume and nutrients. However, current methods suffer from limited multi-view…
STARE-VLA: Progressive Stage-Aware Reinforcement for Fine-Tuning Vision-Language-Action Models
Feng Xu, Guangyao Zhai, Xin Kong +4
Recent advances in Vision-Language-Action (VLA) models, powered by large language models and reinforcement learning-based fine-tuning, have shown remarkable progress in robotic man…
RayPose: Ray Bundling Diffusion for Template Views in Unseen 6D Object Pose Estimation
Junwen Huang, Shishir Reddy Vutukur, Peter KT Yu +3
Typical template-based object pose pipelines estimate the pose by retrieving the closest matching template and aligning it with the observed image. However, failure to retrieve the…
Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors
Guangyao Zhai, Yue Zhou, Xinyan Deng +3
Few-shot anomaly detection streamlines and simplifies industrial safety inspection. However, limited samples make accurate differentiation between normal and abnormal features chal…
MS-CLR: Multi-Skeleton Contrastive Learning for Human Action Recognition
Mert Kiray, Alvaro Ritter, Nassir Navab +1
Contrastive learning has gained significant attention in skeleton-based action recognition for its ability to learn robust representations from unlabeled data. However, existing me…
PromptVFX: Text-Driven Fields for Open-World 3D Gaussian Animation
Mert Kiray, Paul Uhlenbruck, Nassir Navab +1
Visual effects (VFX) are key to immersion in modern films, games, and AR/VR. Creating 3D effects requires specialized expertise and training in 3D animation software and can be tim…
XYZ-IBD: Benchmarking Robust 6D Object Pose Estimation under Real-World Industrial Complexity
Junwen Huang, Jiaqi Hu, Peter KT Yu +3
While current 6D pose estimation benchmarks have reached near-saturation on household objects, they often fail to capture the stochastic and optical complexities of industrial envi…
EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding
Ege Özsoy, Arda Mamur, Felix Tristram +4
Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-paced, occlusion-heavy environment, necessitating advanced perception models to en…
LiteTracker: Leveraging Temporal Causality for Accurate Low-latency Tissue Tracking
Mert Asim Karaoglu, Wenbo Ji, Ahmed Abbas +3
Tissue tracking plays a critical role in various surgical navigation and extended reality (XR) applications. While current methods trained on large synthetic datasets achieve high…
PRISM-0: A Predicate-Rich Scene Graph Generation Framework for Zero-Shot Open-Vocabulary Tasks
Abdelrahman Elskhawy, Mengze Li, Nassir Navab +1
In Scene Graph Generation (SGG), structured representations are extracted from visual inputs as object nodes and connecting predicates, enabling image-based reasoning for diverse d…
FA-BARF: Frequency Adapted Bundle-Adjusting Neural Radiance Fields
Rui Qian, Chenyangguang Zhang, Yan Di +5
Neural Radiance Fields (NeRF) have exhibited highly effective performance for photorealistic novel view synthesis recently. However, the key limitation it meets is the reliance on…
MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Ege Özsoy, Chantal Pellegrini, Tobias Czempiel +7
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipment for enhancing surgical assista…
GCE-Pose: Global Context Enhancement for Category-level Object Pose Estimation
Weihang Li, Hongli Xu, Junwen Huang +4
A key challenge in model-free category-level pose estimation is the extraction of contextual object features that generalize across varying instances within a specific category. Re…
SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark
HyunJun Jung, Weihang Li, Shun-Cheng Wu +8
Traditionally, 3d indoor datasets have generally prioritized scale over ground-truth accuracy in order to obtain improved generalization. However, using these datasets to evaluate…
EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusion
Guangyao Zhai, Evin Pınar Örnek, Dave Zhenyu Chen +5
We present EchoScene, an interactive and controllable generative model that generates 3D indoor scenes on scene graphs. EchoScene leverages a dual-branch diffusion model that dynam…
FLex: Joint Pose and Dynamic Radiance Fields Optimization for Stereo Endoscopic Videos
Florian Philipp Stilz, Mert Asim Karaoglu, Felix Tristram +3
Reconstruction of endoscopic scenes is an important asset for various medical applications, from post-surgery analysis to educational training. Neural rendering has recently shown…
Zero123-6D: Zero-shot Novel View Synthesis for RGB Category-level 6D Pose Estimation
Francesco Di Felice, Alberto Remus, Stefano Gasperini +5
Estimating the pose of objects through vision is essential to make robotic platforms interact with the environment. Yet, it presents many challenges, often related to the lack of f…
MatchU: Matching Unseen Objects for 6D Pose Estimation from RGB-D Images
Junwen Huang, Hao Yu, Kuan-Ting Yu +3
Recent learning methods for object pose estimation require resource-intensive training for each individual object instance or category, hampering their scalability in real applicat…
Deformable 3D Gaussian Splatting for Animatable Human Avatars
HyunJun Jung, Nikolas Brasch, Jifei Song +5
Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonl…
S2P3: Self-Supervised Polarimetric Pose Prediction
Patrick Ruhkamp, Daoyi Gao, Nassir Navab +1
This paper proposes the first self-supervised 6D object pose prediction from multimodal RGB+polarimetric images. The novel training paradigm comprises 1) a physical model to extrac…
RaDialog: A Large Vision-Language Model for Radiology Report Generation and Conversational Assistance
Chantal Pellegrini, Ege Özsoy, Benjamin Busam +2
Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology. Such a human-in-the-…
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation
Yamei Chen, Yan Di, Guangyao Zhai +6
Category-level object pose estimation, aiming to predict the 6D pose and 3D size of objects from known categories, typically struggles with large intra-class shape variation. Exist…