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20232026
most citedDepth-discriminative Metric Learning for Monocular 3D Object Detection

2 citations · 5 across the 8 of their papers we have counts for

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cs.CV2026

CRAFT: Constrained Reward via Attention Fine-Tuning for Subject Personalization without Composed Targets

Jihun Park, Kyoungmin Lee, Jongmin Gim +6

Subject-driven image personalization---generating new images that preserve the identity of one or several reference subjects in novel scenes---is a foundational capability for mode…

cs.CV2025

Temporal Grounding as a Learning Signal for Referring Video Object Segmentation

Seunghun Lee, Jiwan Seo, Jeonghoon Kim +9

Referring Video Object Segmentation (RVOS) aims to segment and track objects in videos based on natural language expressions, requiring precise alignment between visual content and…

cs.CV2024

Flow4D: Leveraging 4D Voxel Network for LiDAR Scene Flow Estimation

Jaeyeul Kim, Jungwan Woo, Ukcheol Shin +2

Understanding the motion states of the surrounding environment is critical for safe autonomous driving. These motion states can be accurately derived from scene flow, which capture…

cs.CV2024

Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator

Wonhyeok Choi, Mingyu Shin, Hyukzae Lee +3

Real-time processing is crucial in autonomous driving systems due to the imperative of instantaneous decision-making and rapid response. In real-world scenarios, autonomous vehicle…

cs.CV20242 cited

Depth-discriminative Metric Learning for Monocular 3D Object Detection

Wonhyeok Choi, Mingyu Shin, Sunghoon Im

Monocular 3D object detection poses a significant challenge due to the lack of depth information in RGB images. Many existing methods strive to enhance the object depth estimation…

cs.CV20231 cited

Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems

SungHo Moon, JinWoo Bae, SungHoon Im

Research on monocular 3D object detection is being actively studied, and as a result, performance has been steadily improving. However, 3D object detection performance is significa…