Search Results for author:
Found 9 papers, 6 papers with code
AntEval: Evaluation of Social Interaction Competencies in LLM-Driven Agents
To address this challenge, we introduce the Multi-Agent Interaction Evaluation Framework (AntEval), encompassing a novel interaction framework and evaluation methods.
IcoCap: Improving Video Captioning by Compounding Images
Video captioning is a more challenging task compared to image captioning, primarily due to differences in content density.
Ranked #5 on
Video Captioning
on VATEX
(using extra training data)
Tachikuma: Understading Complex Interactions with Multi-Character and Novel Objects by Large Language Models
MOE challenges models to understand characters' intentions and accurately determine their actions within intricate contexts involving multi-character and novel object interactions.
MAAL: Multimodality-Aware Autoencoder-Based Affordance Learning for 3D Articulated Objects
Experimental results and visualizations, based on a large-scale dataset PartNet-Mobility, show the effectiveness of MAAL in learning multi-modal data and solving the 3D articulated object affordance problem.
Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification
Second, we instantiate the loss function and provide a strong baseline for FGVC, where the performance of a naive backbone can be boosted and be comparable with recent methods.
Ranked #27 on
Fine-Grained Image Classification
on CUB-200-2011
Fine-Grained Image Classification
Fine-Grained Visual Recognition
SEEG: Semantic Energized Co-Speech Gesture Generation
Talking gesture generation is a practical yet challenging task which aims to synthesize gestures in line with speech.
Ranked #6 on
Gesture Generation
on TED Gesture Dataset
A Simple Episodic Linear Probe Improves Visual Recognition in the Wild
In this paper, we propose an episodic linear probing (ELP) classifier to reflect the generalization of visual representations in an online manner.
Ranked #13 on
Fine-Grained Image Classification
on CUB-200-2011
Removing Raindrops and Rain Streaks in One Go
First, we propose a complementary cascaded network architecture, namely CCN, to remove rain streaks and raindrops in a unified framework.
VrR-VG: Refocusing Visually-Relevant Relationships
Relationships encode the interactions among individual instances, and play a critical role in deep visual scene understanding.
