64 citations · 103 across the 10 of their papers we have counts for
14 papers
FPD-Drive: Future Policy Distillation for End-to-End Autonomous Driving
Li-Heng Chen, Qifeng Chen, Chengwei Wu +4
End-to-end autonomous driving models are typically trained on real-world driving logs, which record only the trajectory actually executed in each scene. This provides limited super…
USR-Drive: Unified Driving Scene Representation via Joint Denoising of 3D Gaussians and Boxes
Li-Heng Chen, Haokai Pang, Chengye Su +7
Spatial representation learning for autonomous driving aims to map raw visual signals into structured 3D scene representations, where object-centric bounding boxes and rendering-or…
VistaGEN: Consistent Driving Video Generation with Fine-Grained Control Using Multiview Visual-Language Reasoning
Li-Heng Chen, Ke Cheng, Yahui Liu +3
Driving video generation has achieved much progress in controllability, video resolution, and length, but fails to support fine-grained object-level controllability for diverse dri…
Learning Perceptual Representations for Gaming NR-VQA with Multi-Task FR Signals
Yu-Chih Chen, Michael Wang, Chieh-Dun Wen +4
No-reference video quality assessment (NR-VQA) for gaming videos is challenging due to limited human-rated datasets and unique content characteristics including fast motion, styliz…
Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videos
Qi Zheng, Li-Heng Chen, Chenlong He +6
Although there have been notable advancements in video compression technologies in recent years, banding artifacts remain a serious issue affecting the quality of compressed videos…
GCRayDiffusion: Pose-Free Surface Reconstruction via Geometric Consistent Ray Diffusion
Li-Heng Chen, Zi-Xin Zou, Chang Liu +5
Accurate surface reconstruction from unposed images is crucial for efficient 3D object or scene creation. However, it remains challenging, particularly for the joint camera pose es…
Estimating the Resize Parameter in End-to-end Learned Image Compression
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
We describe a search-free resizing framework that can further improve the rate-distortion tradeoff of recent learned image compression models. Our approach is simple: compose a pai…
Convolutional Block Design for Learned Fractional Downsampling
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values. However, in many imag…
Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models
Zhengzhong Tu, Chia-Ju Chen, Li-Heng Chen +4
Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus. However, recent ef…
Perceptual Video Quality Prediction Emphasizing Chroma Distortions
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
Measuring the quality of digital videos viewed by human observers has become a common practice in numerous multimedia applications, such as adaptive video streaming, quality monito…
Perceptually Optimizing Deep Image Compression
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
Mean squared error (MSE) and norms have largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used…
A Comparative Evaluation of Temporal Pooling Methods for Blind Video Quality Assessment
Zhengzhong Tu, Chia-Ju Chen, Li-Heng Chen +3
Many objective video quality assessment (VQA) algorithms include a key step of temporal pooling of frame-level quality scores. However, less attention has been paid to studying the…
Facial Emotion Recognition Using Deep Learning
Ching-Da Wu, Li-Heng Chen
We aim to construct a system that captures real-world facial images through the front camera on a laptop. The system is capable of processing/recognizing the captured image and pre…
ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression
Li-Heng Chen, Christos G. Bampis, Zhi Li +2
The use of norms has largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used to assess…