activity
20162025
most citedTemporal Segment Networks: Towards Good Practices for Deep Action Recognition

289 citations · 816 across the 29 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.CV2025

RICO: Two Realistic Benchmarks and an In-Depth Analysis for Incremental Learning in Object Detection

Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Pani Paudel +1

Incremental Learning (IL) trains models sequentially on new data without full retraining, offering privacy, efficiency, and scalability. IL must balance adaptability to new data wi…

cs.CV20251 cited

RoHOI: Robustness Benchmark for Human-Object Interaction Detection

Di Wen, Kunyu Peng, Kailun Yang +7

Human-Object Interaction (HOI) detection is crucial for robot-human assistance, enabling context-aware support. However, models trained on clean datasets degrade in real-world cond…

cs.CV20251 cited

SceneSplat++: A Large Dataset and Comprehensive Benchmark for Language Gaussian Splatting

Mengjiao Ma, Qi Ma, Yue Li +10

3D Gaussian Splatting (3DGS) serves as a highly performant and efficient encoding of scene geometry, appearance, and semantics. Moreover, grounding language in 3D scenes has proven…

cs.CV2025

EarthMind: Leveraging Cross-Sensor Data for Advanced Earth Observation Interpretation with a Unified Multimodal LLM

Yan Shu, Bin Ren, Zhitong Xiong +5

Earth Observation (EO) data analysis is vital for monitoring environmental and human dynamics. Recent Multimodal Large Language Models (MLLMs) show potential in EO understanding bu…

cs.CV2025

One2Any: One-Reference 6D Pose Estimation for Any Object

Mengya Liu, Siyuan Li, Ajad Chhatkuli +3

6D object pose estimation remains challenging for many applications due to dependencies on complete 3D models, multi-view images, or training limited to specific object categories.…

cs.CV2025

SIGHT: Synthesizing Image-Text Conditioned and Geometry-Guided 3D Hand-Object Trajectories

Alexey Gavryushin, Alexandros Delitzas, Luc Van Gool +3

When humans grasp an object, they naturally form trajectories in their minds to manipulate it for specific tasks. Modeling hand-object interaction priors holds significant potentia…