Search Results for author:
Found 7 papers, 3 papers with code
AGL-NET: Aerial-Ground Cross-Modal Global Localization with Varying Scales
We present AGL-NET, a novel learning-based method for global localization using LiDAR point clouds and satellite maps.
On the Safety Concerns of Deploying LLMs/VLMs in Robotics: Highlighting the Risks and Vulnerabilities
However, such integration can introduce significant vulnerabilities, in terms of their susceptibility to adversarial attacks due to the language models, potentially leading to catastrophic consequences.
HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models
Our comprehensive case studies within HallusionBench shed light on the challenges of hallucination and illusion in LVLMs.
Ranked #1 on
Visual Question Answering (VQA)
on HallusionBench
PLAR: Prompt Learning for Action Recognition
We evaluate our approach on datasets consisting of both ground camera videos and aerial videos, and scenes with single-agent and multi-agent actions.
Ranked #1 on
Action Recognition
on Okutama-Action
PMI Sampler: Patch Similarity Guided Frame Selection for Aerial Action Recognition
Our algorithm utilizes the motion bias within aerial videos, which enables the selection of motion-salient frames.
Ranked #1 on
Action Recognition
on UAV-Human
MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition
We present a novel approach for action recognition in UAV videos.
Ranked #2 on
Action Recognition
on UAV-Human
AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning
We propose a novel approach for aerial video action recognition.
Ranked #1 on
Action Recognition
on RoCoG-v2
