9 citations · 29 across the 15 of their papers we have counts for
15 papers
Where to Look Matters: Learning Influential Views for VLM-based 3D Visual Grounding
Tsung-Chih Chiang, Hsuan-Kung Yang, Jou-Min Liu +4
Recent zero-shot 3D visual grounding methods leverage vision-language models (VLMs) to localize objects in 3D scenes from natural language queries. However, these methods typically…
CaST-Bench: Benchmarking Causal Chain-Grounded Spatio-Temporal Reasoning for Video Question Answering
Mingfang Zhang, Jingjing Pan, Ashutosh Kumar +7
Cause-and-effect reasoning in video is a significant challenge for Vision-Language Models (VLMs), as it requires going beyond surface-level perception to a deeper understanding of…
An Embodied AR Navigation Agent: Integrating BIM with Retrieval-Augmented Generation for Language Guidance
Hsuan-Kung Yang, Tsu-Ching Hsiao, Ryoichiro Oka +3
Delivering intelligent and adaptive navigation assistance in augmented reality (AR) requires more than visual cues, as it demands systems capable of interpreting flexible user inte…
Reprojection Errors as Prompts for Efficient Scene Coordinate Regression
Ting-Ru Liu, Hsuan-Kung Yang, Jou-Min Liu +5
Scene coordinate regression (SCR) methods have emerged as a promising area of research due to their potential for accurate visual localization. However, many existing SCR approache…
Visual Forecasting as a Mid-level Representation for Avoidance
Hsuan-Kung Yang, Tsung-Chih Chiang, Ting-Ru Liu +3
The challenge of navigation in environments with dynamic objects continues to be a central issue in the study of autonomous agents. While predictive methods hold promise, their rel…
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)
Tsu-Ching Hsiao, Hao-Wei Chen, Hsuan-Kung Yang +1
Addressing pose ambiguity in 6D object pose estimation from single RGB images presents a significant challenge, particularly due to object symmetries or occlusions. In response, we…
Virtual Guidance as a Mid-level Representation for Navigation with Augmented Reality
Hsuan-Kung Yang, Tsung-Chih Chiang, Jou-Min Liu +4
In the context of autonomous navigation, effectively conveying abstract navigational cues to agents in dynamic environments presents significant challenges, particularly when navig…
Pixel-Wise Prediction based Visual Odometry via Uncertainty Estimation
Hao-Wei Chen, Ting-Hsuan Liao, Hsuan-Kung Yang +1
This paper introduces pixel-wise prediction based visual odometry (PWVO), which is a dense prediction task that evaluates the values of translation and rotation for every pixel in…
Investigation of Factorized Optical Flows as Mid-Level Representations
Hsuan-Kung Yang, Tsu-Ching Hsiao, Ting-Hsuan Liao +7
In this paper, we introduce a new concept of incorporating factorized flow maps as mid-level representations, for bridging the perception and the control modules in modular learnin…
Mixture of Step Returns in Bootstrapped DQN
Po-Han Chiang, Hsuan-Kung Yang, Zhang-Wei Hong +1
The concept of utilizing multi-step returns for updating value functions has been adopted in deep reinforcement learning (DRL) for a number of years. Updating value functions with…
Flow-based Intrinsic Curiosity Module
Hsuan-Kung Yang, Po-Han Chiang, Min-Fong Hong +1
In this paper, we focus on a prediction-based novelty estimation strategy upon the deep reinforcement learning (DRL) framework, and present a flow-based intrinsic curiosity module…
Never Forget: Balancing Exploration and Exploitation via Learning Optical Flow
Hsuan-Kung Yang, Po-Han Chiang, Kuan-Wei Ho +2
Exploration bonus derived from the novelty of the states in an environment has become a popular approach to motivate exploration for deep reinforcement learning agents in the past…
Visual Relationship Prediction via Label Clustering and Incorporation of Depth Information
Hsuan-Kung Yang, An-Chieh Cheng, Kuan-Wei Ho +2
In this paper, we investigate the use of an unsupervised label clustering technique and demonstrate that it enables substantial improvements in visual relationship prediction accur…
Dynamic Video Segmentation Network
Yu-Syuan Xu, Tsu-Jui Fu, Hsuan-Kung Yang +1
In this paper, we present a detailed design of dynamic video segmentation network (DVSNet) for fast and efficient semantic video segmentation. DVSNet consists of two convolutional…
Virtual-to-Real: Learning to Control in Visual Semantic Segmentation
Zhang-Wei Hong, Chen Yu-Ming, Shih-Yang Su +10
Collecting training data from the physical world is usually time-consuming and even dangerous for fragile robots, and thus, recent advances in robot learning advocate the use of si…