Contains bibliographic (front page) information and a representative drawing (if applicable) for each trademark registration or trademark application published that week. Incluides a list of cancelled and renewed registrations.

The Trademark Image Search API (beta) allows searching Trademark Images using various attributes like feature, accuracy, metricspaces and candidates. This API also allows searching Trademark documents using various metadata attributes like Specimen Description, Filing Description, Filing Basis, Owner's Name, Street Address, etc.

The Trademark Status and Document Retrieval (TSDR) API allows you to make programmatic requests for trademark case status, documents, and images. Beginning on October 2, 2020, you will need an API key to download bulk data from TSDR using the TSDR API. Using API keys will help optimize usage of our TSDR system, which will help enable users like yourself to better access the information you need from TSDR. The below resources will provide you with more information on using the TSDR API.

Contains detailed information on 7.0 million trademark applications filed with or registrations issued by the USPTO between 1870 and 2020.

Contains detailed information on 786,931 assignments and other transactions recorded at the USPTO between 1952 and 2020 and involving 1,491,485 million unique trademark properties.

There are two objectives of this shape retrieval contest:

a) To evaluate partial similarity between query and target objects and retrieve complete 3D models that are relevant to a partial query object.

b) To retrieve 3D models those are relevant to a query depth map. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database.

Task description

The objectives of this shape retrieval contest are to evaluate the performance of 3D shape retrieval approaches on a new generic 3D shape benchmark.

Task description: In response to a given set of queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query.

The objective of this track is to evaluate the performance of 3D shape retrieval approaches on a Generic 3D shape benchmark based on the Google 3D Warehouse.

The objective of this shape retrieval contest is to retrieve 3D models those are relevant to a query range scan. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database.

Task description: In response to a given set of queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query. The set of query consists of range images.

The objective of this shape retrieval contest is to retrieve 3D models those are relevant to a query range scan. This task corresponds to a real life scenario where the query is a 3D range scan of an object acquired from an arbitrary view direction. The algorithm should retrieve the relevant 3D objects from a database.

Task description:
In response to a given set of range scan queries, the task is to evaluate similarity scores with the target models and return an ordered ranked list along with the similarity scores for each query.