Overview

We are very happy to invite recently introduced benchmarks, including GraspM3, SHOW3D, and host a series of challenges. To participate in the challenge, please fill the Google Form and accept the terms and conditions.

Winners and prizes will be announced and awarded during the workshop.

Please see General Rules and Participation and the tracks below for more details.

Timeline

July 20 2026 (Opened)	Challenge data & website release & registration open
Around July 22 2026 (Please refer to each track page for details)	Challenges start
August 26 23:59 GMT	Registration close
August 31 (Please refer to each track page for the specific deadline)	Challenge submission deadline
Around August 31 (Please refer to each track page for details)	Decisions to participants
September 6 2026	Technical Report Deadline for Challenges (Invited Teams)

General Rules and Participation

We must follow the general challenge rules below and more rules can be found on each offical track page.

• To participate in the challenge, please fill the Google Form and accept the terms and conditions.

  • Please DO use your institution's email address. Please DO NOT use your personal email address such as gmail.com, qq.com and 163.com.

  • Each team must register under only one user id/email id. The list of team members can not be changed or rearranged throughout the competition.

  • Each team should use the same email for creating accounts in the evaluation server, and use the team name (in verbatim) in the evaluation servers.

  • Each individual can only participate in one team and should provide the institution email at registration.

  • The team name should be formal and we preserve the rights to change the team name after discussing with teams.

  • Each team will receive a registration email after registration.

  • Teams found to be registered under multiple IDs will be disqualified.

  • For any special cases, please email the organizers.

• The primary contact email is important during registration.

  • We will contact participants via emails once we have an important update.

  • If there are any special reasons or ambiguities that may lead to disputes, please email the organizers first for explanation or approval. Subsequent contact may result in disqualification.

• To encourage fair competition, different tracks may include limits like overall model size, training dataset etc. Details can be found in each track page.

  • Teams may use any publicly available and appropriately licensed data (if allowed by the track) to train their models in addition to the ones provided by the organizers.

  • The daily and overall submission number may be limited based on tracks.

  • The best performance of a team CAN NOT be hidden during the competition. Hiding the best performance may result in warning or even disqualification.

  • Any supervised/unsupervised training on the validation/testing set is not allowed in this competition.

• Reproducibility is the responsibility of the winning teams and we invite all teams to advertise their methods.

  • Winning methods should provide their source code to reproduce their results under strict confidentiality rules if requested by organizers/other participants. If the organizing committee determines that the submitted code runs with errors or does not yield results comparable to those in the final leaderboard and the team is not willing to cooperate, it will be disqualified, and the winning place will go to the next team in the leaderboard.

  • In order for participants to be eligible for competition prizes and be included in the official rankings (to be presented during the workshop and subsequent publications), information about their submission must be provided to organizers. Information may include, but not limited to, details on their method, synthetic and real data use, architecture and training details.

  • For each submission, participants must keep the parameters of their method constant across all testing data for a given track.

  • To be considered a valid candidate in the competition, the method has to beat the baseline by a non-trivial margin. A method is invalid if there is no significant technical changes. For example, if you simply replace a ResNet18 backbone with a ResNet101 backbone, it is not counted as a valid method. The organizers preserve all rights to determine the validity of the method. We will invite all valid teams to advertise their methods via 2-3 page technical report, and or poster presentation.

  • Winners should provide a 2-3 page technical report, winner talk, and poster presentation during the workshop.

Grasp Motion

Grasp motion generation for human-like multi-fingered hands has wide applications in animation, robotic grasping, mixed reality interaction, etc. Therefore, we design a grasp motion generation challenge that aims at producing physically plausible grasp motion trajectories conditioned on 3D input objects.
The challenge is built on the GraspM3 dataset. We have retargeted this dataset to the LinkerHand O6, enabling the challenge to be conducted on the LinkerHand O6 hand. You can obtain the corresponding LinkerHand O6 dataset by filling out the request form. An example for the training and testing of grasp motion generation will be provided prior to the challenge via github (This Repository).

Important Dates

• Submission deadline for results: August 31, 2026 (11:59PM PST)
• Results will be shared during the HANDS workshop at ECCV 2026

Rules

• The evaluation process is conducted in Isaac Gym, and the test set objects are not visible to participants.
• Participants are allowed to adjust simulation parameters, provided they clearly specify all modifications made to the environment. However, please note that altering these parameters may compromise the integrity of the evaluation setup and could result in rollout failures.
• For fair comparisons, only methods trained using the datasets from this challenge are qualified for winning.
• Participants may not use the objects not in the dataset for training, fine-tuning, self-supervised pretraining, or any other form of method development.
• However, Participants may use the objects from the Objaverse dataset or other datasets to evaluate the algorithm before submission.
• Participants are required to generate grasping sequences based on randomized initial hand poses. The range of initial poses can be found in README.md.

SHOW3D

Understanding how hands and objects relate to each other in 3D is central to egocentric perception, AR/VR, and robotic manipulation. Existing contact detection methods primarily focus on binary contact estimation, determining whether hands and objects are in contact. However, real dexterous interactions are usually continuous. Binary contact maps collapse all the rich spatiotemporal structure of hand-object interactions into a single bit, discarding the information needed to model how an interaction approaches, sustains, and releases contact.

Therefore, this challenge requires participants to evaluates dense 3D hand-object interaction field on SHOW3D dataset. The task is per-frame. Given an egocentric frame, participants predict, for each visible hand, a hand-anchored 3D vector field: the offset from every hand joint to the nearest surface point of the manipulated object.

Both single-view and multi-view methods are eligible. Participants must declare their input setting and any external training data in their submission description. The live leaderboard is combined; organizers publish separate final tables for methods with and without external training data.

Important Dates

• Submission deadline for results: August 31, 2026 (4:59PM PDT / 11:59PM GMT / 7:59AM CST next day)
• Results will be shared during the HANDS workshop at ECCV 2026

Terms and Conditions

• Use the SHOW3D dataset only under the release license and access terms: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).
• Do not attempt to recover hidden labels or tune submissions manually against the evaluation server.
• Submissions must be generated by a model or deterministic algorithm that can be described by the participant.