58 citations · 75 across the 9 of their papers we have counts for
7 papers · 1 filter
NeRF-HuGS: Improved Neural Radiance Fields in Non-static Scenes Using Heuristics-Guided Segmentation
Jiahao Chen, Yipeng Qin, Lingjie Liu +2
Neural Radiance Field (NeRF) has been widely recognized for its excellence in novel view synthesis and 3D scene reconstruction. However, their effectiveness is inherently tied to t…
Deep Generative Model based Rate-Distortion for Image Downscaling Assessment
Yuanbang Liang, Bhavesh Garg, Paul L Rosin +1
In this paper, we propose Image Downscaling Assessment by Rate-Distortion (IDA-RD), a novel measure to quantitatively evaluate image downscaling algorithms. In contrast to image-ba…
Feature Proliferation -- the "Cancer" in StyleGAN and its Treatments
Shuang Song, Yuanbang Liang, Jing Wu +2
Despite the success of StyleGAN in image synthesis, the images it synthesizes are not always perfect and the well-known truncation trick has become a standard post-processing techn…
Motion-R3: Fast and Accurate Motion Annotation via Representation-based Representativeness Ranking
Jubo Yu, Tianxiang Ren, Shihui Guo +6
In this paper, we follow a data-centric philosophy and propose a novel motion annotation method based on the inherent representativeness of motion data in a given dataset. Specific…
Diverse Motion In-betweening with Dual Posture Stitching
Tianxiang Ren, Jubo Yu, Shihui Guo +5
In-betweening is a technique for generating transitions given initial and target character states. The majority of existing works require multiple (often 10) frames as input, wh…
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels
Ganlong Zhao, Guanbin Li, Yipeng Qin +2
Deep models trained with noisy labels are prone to over-fitting and struggle in generalization. Most existing solutions are based on an ideal assumption that the label noise is cla…