1.4k citations · 2.6k across the 155 of their papers we have counts for
166 papers · 1 filter
MECAIL: Communication-Aware Incremental Learning for Object Detection with 14.6 KB Spatiotemporal Experts
Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Paudel +3
Intelligent transportation systems require Incremental Learning (IL) to continually improve their overall performance in dynamic environments. However, most edge devices lack the c…
Do LiDAR Language Models Really Understand Spatio-temporal Relationships?
Runyi Yang, Murat Akkoyun, Di Wen +8
Recent 4D LiDAR language models aim to reason about objects and their evolving spatial relationships. Yet, in our evaluation, always selecting the same option nearly matches the mu…
Accelerated Decoding of Centroid Positional Encoding for Instance Segmentation
Carmelo Scribano, Filippo Muzzini, Nedyalko Prisadnikov +6
Beyond model inference, the decoding stage, which converts raw network outputs into task-level representations, constitutes a significant portion of the execution cost. Despite its…
ConeGaussian: Anti-Aliased Gaussian Ray-Tracing for Generic Central Cameras
Deheng Zhang, Letian Shi, Runyi Yang +6
In rendering, a camera is a sampling operator that maps each finite pixel to a bundle of rays. Different camera models change the geometry of this bundle, thus making a unified and…
LangStreet: Persistent Language Fields for Anchor-Decoded Street Gaussians
Runyi Yang, Deheng Zhang, Xiaoye Wang +6
Language Gaussian fields implicitly assume that the primitive carrying semantics remains identifiable across views. This assumption breaks in scalable anchor-decoded representation…
Kairos: A Dataset for Fine-Grained Video-Language Modeling over Space, Time, and Dynamics
Ruibo Ming, Lei Sun, Deheng Zhang +8
Many emerging video language modeling tasks require systems to move beyond clip-level abstraction and model visual content as it unfolds over extended time horizons. However, most…
Event-Based Motion Estimation via Oriented Distance Fields
Lei Sun, Yuqin Ma, Weilun Li +5
Event-based motion estimation is central to tasks that demand high temporal resolution and robustness to fast motion. Existing methods typically rely on iterative optimization or r…
More with Less: a Large Scale Remote Sensing VLM with a Simple Recipe
Stefan Maria Ailuro, Mario Markov, Mohammad Mahdi +2
Remote sensing vision-language models are increasingly expected to support open-ended reasoning over Earth Observation data and a variety of tasks. Most recent progress in this are…
SA-VIS: Sparse frame Annotations for training Video Instance Segmentation
Edoardo Mello Rella, Ajad Chhatkuli, Shipra Jain +2
Recent online video instance segmentation (VIS) methods have achieved impressive results, thus becoming the preferred approach to segment instances in videos. Despite the resurgenc…
Semantic-Aware, Physics-Informed, Geometry-Grounded Weather Video Synthesis
Chenghao Qian, Nedko Savov, Lingdong Kong +7
Weather synthesis aims to add weather effects to input videos while preserving scene identity, structure, and motion. The key limitation of existing methods is the lack of diversit…
The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results
Lei Sun, Hang Guo, Bin Ren +6
This paper reports on the NTIRE 2026 Challenge on Image Denoising, specifically focusing on the high-noise regime (). The competition investigates advanced neural architectu…
B-GRTO: Bootstrapped Group Relative Tool Optimization for Referring Segmentation
Mario Markov, Stefan Maria Ailuro, Mohammad Mahdi +2
Segmentation is a fundamental task in computer vision, underpinning pixel-level scene understanding and serving as a cornerstone for applications ranging from autonomous perception…
Accelerating Vision Foundation Models with Drop-in Depthwise Convolution
Carmelo Scribano, Mohammad Mahdi, Nedyalko Prisadnikov +5
Pretrained vision foundation models deliver strong performance across tasks with limited fine-tuning. However, their Vision Transformer (ViT) backbones impose high inference costs,…
SeasonScapes: Learning Large-scale Re-lightable 3D Landscapes with Seasonal Variation from Sparse Webcams
Timo Kleger, Qi Ma, Deheng Zhang +2
We introduce SeasonScapes framework and a the SeasonScapes dataset: Swiss Sparse-view Mountain Scenes with Seasonal Changes that covers over 50 km x 60 km, composed of more than 85…
From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation
Mohammad Mahdi, Nedko Savov, Danda Pani Paudel +1
Exo-to-Ego video generation aims to synthesize a first-person video from a synchronized third-person view and corresponding camera poses. While paired supervision is available, syn…
OSMDA: OpenStreetMap-based Domain Adaptation for Remote Sensing VLMs
Stefan Maria Ailuro, Mario Markov, Mohammad Mahdi +3
Vision-Language Models (VLMs) adapted to remote sensing rely heavily on domain-specific image-text supervision, yet high-quality annotations for satellite and aerial imagery remain…
Self-Supervised Learning with a Multi-Task Latent Space Objective
Pierre-François De Plaen, Abhishek Jha, Luc Van Gool +2
We propose a multi-task formulation of self-predictive Siamese SSL in which each spatial transformation defines a distinct latent-space alignment task, solved by a dedicated predic…
Inferring Compositional 4D Scenes without Ever Seeing One
Ahmet Berke Gokmen, Ajad Chhatkuli, Luc Van Gool +1
Scenes in the real world are often composed of several static and dynamic objects. Capturing their 4-dimensional structures, composition and spatio-temporal configuration in-the-wi…
EvDiff: Event-Based Video Reconstruction using One-Step Diffusion Models
Weilun Li, Lei Sun, Ruixi Gao +6
As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal resolution and high dynamic rang…
FireScope: Wildfire Risk Raster Prediction with a Chain-of-Thought Oracle
Mario Markov, Stefan Maria Ailuro, Luc Van Gool +2
Predicting wildfire risk is a reasoning-intensive spatial problem that requires the integration of visual, climatic, and geographic factors to infer continuous risk maps. Existing…
DGFusion: Depth-Guided Sensor Fusion for Robust Semantic Perception
Tim Broedermannn, Christos Sakaridis, Luigi Piccinelli +2
Robust semantic perception for autonomous vehicles relies on effectively combining multiple sensors with complementary strengths and weaknesses. State-of-the-art sensor fusion appr…
Incremental Object Detection with Prompt-based Methods
Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Pani Paudel +1
Visual prompt-based methods have seen growing interest in incremental learning (IL) for image classification. These approaches learn additional embedding vectors while keeping the…
Spatial-Temporal Graph Mamba for Music-Guided Dance Video Synthesis
Hao Tang, Ling Shao, Zhenyu Zhang +2
We propose a novel spatial-temporal graph Mamba (STG-Mamba) for the music-guided dance video synthesis task, i.e., to translate the input music to a dance video. STG-Mamba consists…
GaussianVLM: Scene-centric 3D Vision-Language Models using Language-aligned Gaussian Splats for Embodied Reasoning and Beyond
Anna-Maria Halacheva, Jan-Nico Zaech, Xi Wang +2
As multimodal language models advance, their application to 3D scene understanding is a fast-growing frontier, driving the development of 3D Vision-Language Models (VLMs). Current…