activity
20192026
most citedLearning from 2D: Contrastive Pixel-to-Point Knowledge Transfer for 3D Pretraining

24 citations · 92 across the 36 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

cs.RO2024

Context-Aware Replanning with Pre-explored Semantic Map for Object Navigation

Po-Chen Ko, Hung-Ting Su, Ching-Yuan Chen +3

Pre-explored Semantic Maps, constructed through prior exploration using visual language models (VLMs), have proven effective as foundational elements for training-free robotic appl…

cs.CL2024

Unveiling Narrative Reasoning Limits of Large Language Models with Trope in Movie Synopses

Hung-Ting Su, Ya-Ching Hsu, Xudong Lin +5

Large language models (LLMs) equipped with chain-of-thoughts (CoT) prompting have shown significant multi-step reasoning capabilities in factual content like mathematics, commonsen…

cs.LG2024

Revisiting Semi-supervised Adversarial Robustness via Noise-aware Online Robust Distillation

Tsung-Han Wu, Hung-Ting Su, Shang-Tse Chen +1

The robust self-training (RST) framework has emerged as a prominent approach for semi-supervised adversarial training. To explore the possibility of tackling more complicated tasks…

cs.CV2024

HERMES: temporal-coHERent long-forM understanding with Episodes and Semantics

Gueter Josmy Faure, Jia-Fong Yeh, Min-Hung Chen +3

Long-form video understanding presents unique challenges that extend beyond traditional short-video analysis approaches, particularly in capturing long-range dependencies, processi…

cs.CV2024

Investigating Video Reasoning Capability of Large Language Models with Tropes in Movies

Hung-Ting Su, Chun-Tong Chao, Ya-Ching Hsu +4

Large Language Models (LLMs) have demonstrated effectiveness not only in language tasks but also in video reasoning. This paper introduces a novel dataset, Tropes in Movies (TiM),…

cs.LG2024

Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approach

ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1

Traditional traffic prediction, limited by the scope of sensor data, falls short in comprehensive traffic management. Mobile networks offer a promising alternative using network ac…

cs.CV2024

Tel2Veh: Fusion of Telecom Data and Vehicle Flow to Predict Camera-Free Traffic via a Spatio-Temporal Framework

ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1

Vehicle flow, a crucial indicator for transportation, is often limited by detector coverage. With the advent of extensive mobile network coverage, we can leverage mobile user activ…

cs.CV2024

Tracking-Assisted Object Detection with Event Cameras

Ting-Kang Yen, Igor Morawski, Shusil Dangi +5

Event-based object detection has recently garnered attention in the computer vision community due to the exceptional properties of event cameras, such as high dynamic range and no…

cs.RO2024★ 1 cited

AED: Adaptable Error Detection for Few-shot Imitation Policy

Jia-Fong Yeh, Kuo-Han Hung, Pang-Chi Lo +5

We introduce a new task called Adaptable Error Detection (AED), which aims to identify behavior errors in few-shot imitation (FSI) policies based on visual observations in novel en…

cs.LG2024

TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling

ChungYi Lin, Shen-Lung Tung, Hung-Ting Su +1

To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensiv…