2 citations · 2 across the 5 of their papers we have counts for
5 papers
PointSplat: Efficient Geometry-Driven Pruning and Transformer Refinement for 3D Gaussian Splatting
Anh Thuan Tran, Jana Kosecka
3D Gaussian Splatting (3DGS) has recently unlocked real-time, high-fidelity novel view synthesis by representing scenes using explicit 3D primitives. However, traditional methods o…
TRAVEL: Training-Free Retrieval and Alignment for Vision-and-Language Navigation
Navid Rajabi, Jana Kosecka
In this work, we propose a modular approach for the Vision-Language Navigation (VLN) task by decomposing the problem into four sub-modules that use state-of-the-art Large Language…
GSR-BENCH: A Benchmark for Grounded Spatial Reasoning Evaluation via Multimodal LLMs
Navid Rajabi, Jana Kosecka
The ability to understand and reason about spatial relationships between objects in images is an important component of visual reasoning. This skill rests on the ability to recogni…
Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM
Navid Rajabi, Jana Kosecka
Vision and Language Models (VLMs) continue to demonstrate remarkable zero-shot (ZS) performance across various tasks. However, many probing studies have revealed that even the best…
Labeling Indoor Scenes with Fusion of Out-of-the-Box Perception Models
Yimeng Li, Navid Rajabi, Sulabh Shrestha +2
The image annotation stage is a critical and often the most time-consuming part required for training and evaluating object detection and semantic segmentation models. Deployment o…