21 citations · 31 across the 6 of their papers we have counts for
9 papers · 1 filter
GeoSURGE: Geo-localization using Semantic Fusion with Hierarchy of Geographic Embeddings
Angel Daruna, Nicholas Meegan, Han-Pang Chiu +2
Worldwide visual geo-localization aims to determine the geographic location of an image anywhere on Earth using only its visual content. Despite recent progress, learning expressiv…
Efficient Domain-Adaptive Multi-Task Dense Prediction with Vision Foundation Models
Beomseok Kang, Niluthpol Chowdhury Mithun, Mikhail Sizintsev +2
Multi-task dense prediction, which aims to jointly solve tasks like semantic segmentation and depth estimation, is crucial for robotics applications but suffers from domain shift w…
DUDA: Distilled Unsupervised Domain Adaptation for Lightweight Semantic Segmentation
Beomseok Kang, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi +2
Unsupervised Domain Adaptation (UDA) is essential for enabling semantic segmentation in new domains without requiring costly pixel-wise annotations. State-of-the-art (SOTA) UDA met…
Diffusion-Guided Gaussian Splatting for Large-Scale Unconstrained 3D Reconstruction and Novel View Synthesis
Niluthpol Chowdhury Mithun, Tuan Pham, Qiao Wang +6
Recent advancements in 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have achieved impressive results in real-time 3D reconstruction and novel view synthesis. Howe…
GraphMapper: Efficient Visual Navigation by Scene Graph Generation
Zachary Seymour, Niluthpol Chowdhury Mithun, Han-Pang Chiu +2
Understanding the geometric relationships between objects in a scene is a core capability in enabling both humans and autonomous agents to navigate in new environments. A sparse, u…
MaAST: Map Attention with Semantic Transformersfor Efficient Visual Navigation
Zachary Seymour, Kowshik Thopalli, Niluthpol Mithun +3
Visual navigation for autonomous agents is a core task in the fields of computer vision and robotics. Learning-based methods, such as deep reinforcement learning, have the potentia…