activity
20202026
most citedLearning a Domain-Agnostic Visual Representation for Autonomous Driving via Contrastive Loss

3 citations · 11 across the 16 of their papers we have counts for

collaborators

19 papers

cs.RO2026

LYRIC: Language-Driven Physics-Based Character Control for Contact-Rich Whole-Body Object Interaction

Zeyu Han, Zichong Meng, Julian Tanke +8

We present LYRIC, a generative flow-matching controller for language-driven physics-based contact-rich interaction control, that enables simulated characters to perform contact-ric…

cs.CV2026

Odoriko: A Shape-Aware Multimodal Diffusion Framework for Human Motion

Dongseok Shim, Julian Tanke, Kengo Uchida +5

Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into single multimodal frameworks. Ho…

cs.CV2026

PTC-Depth: Pose-Refined Monocular Depth Estimation with Temporal Consistency

Leezy Han, Seunggyu Kim, Dongseok Shim +1

Monocular depth estimation (MDE) has been widely adopted in the perception systems of autonomous vehicles and mobile robots. However, existing approaches often struggle to maintain…

cs.LG2026

EUGens: Efficient, Unified, and General Dense Layers

Sang Min Kim, Byeongchan Kim, Arijit Sehanobish +7

Efficient neural networks are essential for scaling machine learning models to real-time applications and resource-constrained environments. Fully-connected feedforward layers (FFL…

cs.CV2026

Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models

Christian Simon, Masato Ishii, Wei-Yao Wang +8

Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and frame-level video information.…

cs.LG2025

Periodic Skill Discovery

Jonghae Park, Daesol Cho, Jusuk Lee +3

Unsupervised skill discovery in reinforcement learning (RL) aims to learn diverse behaviors without relying on external rewards. However, current methods often overlook the periodi…