20 citations · 42 across the 6 of their papers we have counts for
6 papers
MVA 2025 Small Multi-Object Tracking for Spotting Birds Challenge: Dataset, Methods, and Results
Yuki Kondo, Norimichi Ukita, Riku Kanayama +21
Small Multi-Object Tracking (SMOT) is particularly challenging when targets occupy only a few dozen pixels, rendering detection and appearance-based association unreliable. Buildin…
Robot Motion Planning using One-Step Diffusion with Noise-Optimized Approximate Motions
Tomoharu Aizu, Takeru Oba, Yuki Kondo +1
This paper proposes an image-based robot motion planning method using a one-step diffusion model. While the diffusion model allows for high-quality motion generation, its computati…
NTIRE 2023 Image Shadow Removal Challenge Technical Report: Team IIM_TTI
Yuki Kondo, Riku Miyata, Fuma Yasue +2
In this paper, we analyze and discuss ShadowFormer in preparation for the NTIRE2023 Shadow Removal Challenge [1], implementing five key improvements: image alignment, the introduct…
MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results
Yuki Kondo, Norimichi Ukita, Takayuki Yamaguchi +19
Small Object Detection (SOD) is an important machine vision topic because (i) a variety of real-world applications require object detection for distant objects and (ii) SOD is a ch…
Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images
Yuki Kondo, Norimichi Ukita
This paper proposes crack segmentation augmented by super resolution (SR) with deep neural networks. In the proposed method, a SR network is jointly trained with a binary segmentat…
Kernelized Back-Projection Networks for Blind Super Resolution
Tomoki Yoshida, Yuki Kondo, Takahiro Maeda +2
Since non-blind Super Resolution (SR) fails to super-resolve Low-Resolution (LR) images degraded by arbitrary degradations, SR with the degradation model is required. However, this…