Papers Event Segmentation
“Event Segmentation” 태그가 달린 논문 34편 · 필터 해제
Adaptive Multi-Granularity Temporal Modeling for Weakly Supervised Video Anomaly Detection
As the scale of video surveillance data outpaces manual annotation capacities, weakly supervised video anomaly detection (WSVAD) has emerged as a critical research frontier. Most existing approaches formulate WSVAD withi…
Multiple Instance LearningVideo Anomaly DetectionEvent SegmentationWorth Remembering: Surprise-Gated Robot Episodic Memory
Robots solving generalist tasks need to be able to ground instructions in their past experience, since humans may refer to notable past events when giving a task (e.g., ``Take me to where the chemical spill happened yest…
Event SegmentationQuestion AnsweringHingeMem: Boundary Guided Long-Term Memory with Query Adaptive Retrieval for Scalable Dialogues
Long-term memory is critical for dialogue systems that support continuous, sustainable, and personalized interactions. However, existing methods rely on continuous summarization or OpenIE-based graph construction paired …
Event SegmentationQuestion AnsweringLoss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
High-quality video datasets are foundational for training robust models in tasks like action recognition, phase detection, and event segmentation. However, many real-world video datasets suffer from annotation errors suc…
Event SegmentationAction RecognitionVideo SegmentationSegment Any Events with Language
Scene understanding with free-form language has been widely explored within diverse modalities such as images, point clouds, and LiDAR. However, related studies on event sensors are scarce or narrowly centered on semanti…
Instance SegmentationScene UnderstandingEvent SegmentationPoint CloudsES-Mem: Event Segmentation-Based Memory for Long-Term Dialogue Agents
Memory is critical for dialogue agents to maintain coherence and enable continuous adaptation in long-term interactions. While existing memory mechanisms offer basic storage and retrieval capabilities, they are hindered …
Semantic SimilarityEvent SegmentationMemory Matters More: Event-Centric Memory as a Logic Map for Agent Searching and Reasoning
Large language models (LLMs) are increasingly deployed as intelligent agents that reason, plan, and interact with their environments. To effectively scale to long-horizon scenarios, a key capability for such agents is a …
Semantic RetrievalEvent SegmentationVideoScaffold: Elastic-Scale Visual Hierarchies for Streaming Video Understanding in MLLMs
Understanding long videos with multimodal large language models (MLLMs) remains challenging due to the heavy redundancy across frames and the need for temporally coherent representations. Existing static strategies, such…
Event SegmentationCambrian-S: Towards Spatial Supersensing in Video
We argue that progress in true multimodal intelligence calls for a shift from reactive, task-driven systems and brute-force long context towards a broader paradigm of supersensing. We frame spatial supersensing as four s…
Event SegmentationOnline Generic Event Boundary Detection
Generic Event Boundary Detection (GEBD) aims to interpret long-form videos through the lens of human perception. However, current GEBD methods require processing complete video frames to make predictions, unlike humans p…
Generic Event Boundary DetectionEvent SegmentationAdaptive Event Stream Slicing for Open-Vocabulary Event-Based Object Detection via Vision-Language Knowledge Distillation
Event cameras offer advantages in object detection tasks due to high-speed response, low latency, and robustness to motion blur. However, event cameras lack texture and color information, making open-vocabulary detection…
Knowledge DistillationEvent SegmentationObject DetectionAW-GATCN: Adaptive Weighted Graph Attention Convolutional Network for Event Camera Data Joint Denoising and Object Recognition
Event cameras, which capture brightness changes with high temporal resolution, inherently generate a significant amount of redundant and noisy data beyond essential object structures. The primary challenge in event-based…
DenoisingEvent SegmentationGraph AttentionObject+1Open-World Skill Discovery from Unsegmented Demonstrations
Learning skills in open-world environments is essential for developing agents capable of handling a variety of tasks by combining basic skills. Online demonstration videos are typically long but unsegmented, making them …
Boundary DetectionEvent SegmentationInstruction FollowingMinecraft+3Event Segmentation Applications in Large Language Model Enabled Automated Recall Assessments
Understanding how individuals perceive and recall information in their natural environments is critical to understanding potential failures in perception (e.g., sensory loss) and memory (e.g., dementia). Event segmentati…
Event SegmentationLanguage ModelingLanguage ModellingLarge Language Model+3Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos
Self-supervised learning holds the promise to learn good representations from real-world continuous uncurated data streams. However, most existing works in visual self-supervised learning focus on static images or artifi…
Continual LearningContrastive LearningEvent SegmentationSelf-Supervised LearningA Review of Mechanistic Models of Event Comprehension
This review examines theoretical assumptions and computational models of event comprehension, tracing the evolution from discourse comprehension theories to contemporary event cognition frameworks. The review covers key …
Event SegmentationRepresentation LearningHuman-like Episodic Memory for Infinite Context LLMs
Large language models (LLMs) have shown remarkable capabilities, but still struggle with processing extensive contexts, limiting their ability to maintain coherence and accuracy over long sequences. In contrast, the huma…
Computational EfficiencyEvent SegmentationRAGRetrievalDescription and analysis of novelties introduced in DCASE Task 4 2022 on the baseline system
The aim of the Detection and Classification of Acoustic Scenes and Events Challenge Task 4 is to evaluate systems for the detection of sound events in domestic environments using an heterogeneous dataset. The systems nee…
Event SegmentationPredictive Event Segmentation and Representation with Neural Networks: A Self-Supervised Model Assessed by Psychological Experiments
People segment complex, ever-changing and continuous experience into basic, stable and discrete spatio-temporal experience units, called events. Event segmentation literature investigates the mechanisms that allow people…
Event SegmentationSegmentationDeveloping hierarchical anticipations via neural network-based event segmentation
Humans can make predictions on various time scales and hierarchical levels. Thereby, the learning of event encodings seems to play a crucial role. In this work we model the development of hierarchical predictions via aut…
Event SegmentationInductive Learning