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Understanding human-object interaction (HOI) in videos represents a fundamental yet intricate challenge in computer vision, requiring perception and reasoning across both spatial and temporal domains. Despite previous success of object detection ...$$${}_{\mathrm{}}$

In recent years, domain adaptation techniques have been widely used to adapt face anti-spoofing models to a cross-scenario target domain. Most previous methods assume that the Presentation Attack Instruments (PAIs) in such cross-scenario target domains ...

Surgical triplet recognition aims to recognize surgical activities as triplets (i.e.,<instrument, verb, target >), which provides fine-grained information essential for surgical scene understanding. Existing methods for surgical triplet recognition rely ...

Product search for online shopping should be season-aware, i.e., presenting seasonally relevant products to customers. In this paper, we propose a simple yet effective solution to improve seasonal relevance in product search by incorporating seasonality ...

In this paper, we tackle the 3D object representation learning from the perspective of set-to-set matching. Given two 3D objects, calculating their similarity is formulated as the problem of set-to-set similarity measurement between two set of local ...

As we use our hands frequently in daily activities, the analysis of hand-object interactions plays a critical role to many multimedia understanding and interaction applications. Different from conventional 3D hand-only and object-only pose estimation, ...

Product quantization has been widely used in fast image retrieval due to its effectiveness of coding high-dimensional visual features. By constructing the approximation function, we extend the hard-assignment quantization to soft-assignment ...

Spatiotemporal irregularities (i.e., the uncommon appearance and motion patterns) in videos are difficult to detect, as they are usually not well defined and appear rarely in videos. We tackle this problem by learning normal patterns ...

One of the key challenges of machine learning-based anomaly detection relies on the difficulty of obtaining anomaly data for training, which is usually rare, diversely distributed, and difficult to collect. To address this challenge, we formulate anomaly ...

Embedding high-dimensional visual features (d-dimensional) to binary codes (b-dimensional) has shown advantages in various vision tasks such as object recognition and image retrieval. Meanwhile, recent works have demonstrated that to fully utilize the ...

Approximate nearest neighbor (ANN) search is a fundamental problem in computer vision, machine learning and information retrieval. Recently, quantization-based methods have drawn a lot of attention due to their superior accuracy and comparable efficiency ...

This paper addresses the problem of videolevel object instance search, which aims to retrieve the videos in the database that contain a given query object instance. Without prior knowledge about "when" and "where" an object of interest may appear in a ...

Given a specific object as query, object instance search aims to not only retrieve the images or frames that contain the query, but also locate all its occurrences. In this work, we explore the use of spatio-temporal cues to improve the quality of object ...

We present an efficient approach to search for and locate all occurrences of a specific object in large video volumes, given a single query example. Locations of object occurrences are returned as spatio-temporal trajectories in the 3D video volume. ...

Searching visual objects in large image or video data sets is a challenging problem, because it requires efficient matching and accurate localization of query objects that often occupy a small part of an image. Although spatial context has been shown to ...

The recently developed depth sensors, e.g., the Kinect sensor, have provided new opportunities for human-computer interaction (HCI). Although great progress has been made by leveraging the Kinect sensor, e.g., in human body tracking, face recognition ...

Visual object search, with the goal to find and locate the target object in large image or video collections, is of great interest for many applications and hence has received intensive attentions in recent years. In this demo, we present a spatial ...

Hand gesture based Human-Computer-Interaction (HCI) is one of the most natural and intuitive ways to communicate between people and machines, since it closely mimics how human interact with each other. In this demo, we present a hand gesture recognition ...

Searching for small objects (e.g., logos) in images is a critical yet challenging problem. It becomes more difficult when target objects differ significantly from the query object due to changes in scale, viewpoint or style, not to mention partial ...

Recurring events are short temporal patterns that consist of multiple instances in the target database. Without any a priori knowledge of the recurring events, in terms of their lengths, temporal locations, the total number of such events, and possible ...