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20182026
most citedMultiResolution Attention Extractor for Small Object Detection

8 citations · 14 across the 23 of their papers we have counts for

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25 papers · 1 filter

cs.CV2026

SeGDeP: Semantic- and Geometric-Aware Decoupled Prompts for Reasoning Segmentation

Linnan Zhao, Xu Liu, Lingling Li +3

Reasoning segmentation converts an implicit linguistic conclusion into a precise mask, requiring both semantic identification and spatial grounding. Existing MLLM-segmenter interfa…

cs.CV2026

Solution for UCF UrbanTwin V2X-Real Track: Sim-to-Real Urban LiDAR 3D Object Detection

Pu Luo, Cong Xu, Yumei Li +4

Bridging the simulation-to-reality gap in roadside LiDAR requires addressing several coupled discrepancies, including scene geometry, sampling density, return patterns, and pedestr…

cs.CV2026

ExACT: Exemplar-Driven Calibrated Refinement for Training-Free Visual Grounding in Remote Sensing Images

Zixiao Zhang, Lingling Li, Pei He +2

Remote sensing visual grounding (RSVG) aims to locate specific objects in high-resolution RS imagery using free-form natural language descriptions. While recent advances in multimo…

cs.CV2026

DEVIS-GRPO: Unleashing GRPO on Dynamic Extreme View Synthesis

Yi Zuo, Huimin Wu, Lingling Li +3

Trajectory-controlled video generation has become essential for controllable video generation. While current methods perform well under small-view camera motions, they degrade sign…

cs.CV2026

LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)

Wei Luo, Yiting Lu, Xin Li +32

This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and 4D generation settings. The…

cs.CV2026

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

Benjamin Kiefer, Jan Lukas Augustin, Jon Muhovič +52

The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026. This edition features five benchmark challenges with emphasis on both predictive accuracy an…